diff --git a/.gitignore b/.gitignore
index 28ddefaa7f..7940257d13 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,8 +7,6 @@ docs/recipes/*_files/
 docs/examples/*.md
 docs/examples/*/*.md
 docs/examples/*_files/
-docs/benchmarks/*/*.md
-docs/benchmarks/*/*.csv
 docs/api/
 site
 docs/linkified
diff --git a/docs/benchmarks/Binary classification/binary_classification.csv b/docs/benchmarks/Binary classification/binary_classification.csv
new file mode 100644
index 0000000000..4b38617bef
--- /dev/null
+++ b/docs/benchmarks/Binary classification/binary_classification.csv	
@@ -0,0 +1,3637 @@
+step,track,model,dataset,Accuracy,F1,Memory in Mb,Time in s
+106,Binary classification,Logistic regression,Bananas,0.49056603773584906,0.3414634146341463,0.004187583923339844,0.00989
+212,Binary classification,Logistic regression,Bananas,0.5141509433962265,0.3832335329341317,0.004187583923339844,0.123413
+318,Binary classification,Logistic regression,Bananas,0.5220125786163522,0.42424242424242425,0.004240989685058594,0.315017
+424,Binary classification,Logistic regression,Bananas,0.5165094339622641,0.40233236151603496,0.004240989685058594,0.5849610000000001
+530,Binary classification,Logistic regression,Bananas,0.5320754716981132,0.36410256410256414,0.004240989685058594,0.9372130000000001
+636,Binary classification,Logistic regression,Bananas,0.5377358490566038,0.32876712328767127,0.004240989685058594,1.342505
+742,Binary classification,Logistic regression,Bananas,0.5525606469002695,0.3054393305439331,0.004240989685058594,1.8950680000000002
+848,Binary classification,Logistic regression,Bananas,0.5530660377358491,0.28083491461100574,0.004240989685058594,2.518365
+954,Binary classification,Logistic regression,Bananas,0.5555555555555556,0.25874125874125875,0.004240989685058594,3.1930270000000003
+1060,Binary classification,Logistic regression,Bananas,0.5622641509433962,0.2418300653594771,0.004240989685058594,3.938137
+1166,Binary classification,Logistic regression,Bananas,0.5608919382504288,0.22424242424242424,0.004240989685058594,4.7351090000000005
+1272,Binary classification,Logistic regression,Bananas,0.5613207547169812,0.2206703910614525,0.004240989685058594,5.600857
+1378,Binary classification,Logistic regression,Bananas,0.5645863570391872,0.20844327176781002,0.004240989685058594,6.476079
+1484,Binary classification,Logistic regression,Bananas,0.5646900269541779,0.19651741293532338,0.004240989685058594,7.428853
+1590,Binary classification,Logistic regression,Bananas,0.5647798742138365,0.18588235294117644,0.004240989685058594,8.473991
+1696,Binary classification,Logistic regression,Bananas,0.5660377358490566,0.17857142857142858,0.004240989685058594,9.59319
+1802,Binary classification,Logistic regression,Bananas,0.562708102108768,0.17052631578947366,0.004240989685058594,10.745503
+1908,Binary classification,Logistic regression,Bananas,0.5587002096436059,0.16798418972332016,0.004240989685058594,11.962335
+2014,Binary classification,Logistic regression,Bananas,0.5516385302879842,0.16620498614958448,0.004240989685058594,13.252336
+2120,Binary classification,Logistic regression,Bananas,0.5495283018867925,0.1688424717145344,0.004240989685058594,14.603624
+2226,Binary classification,Logistic regression,Bananas,0.5485175202156334,0.18092909535452323,0.004240989685058594,15.981958
+2332,Binary classification,Logistic regression,Bananas,0.5484562607204116,0.19679633867276888,0.004240989685058594,17.395643
+2438,Binary classification,Logistic regression,Bananas,0.5471698113207547,0.19999999999999998,0.004240989685058594,18.850781
+2544,Binary classification,Logistic regression,Bananas,0.5479559748427673,0.21662125340599456,0.004240989685058594,20.422045
+2650,Binary classification,Logistic regression,Bananas,0.5452830188679245,0.2260757867694284,0.004240989685058594,22.049363
+2756,Binary classification,Logistic regression,Bananas,0.5395500725689405,0.22857142857142854,0.004240989685058594,23.763248
+2862,Binary classification,Logistic regression,Bananas,0.5391334730957372,0.230005837711617,0.004240989685058594,25.51638
+2968,Binary classification,Logistic regression,Bananas,0.5411051212938005,0.22613636363636364,0.004240989685058594,27.316788000000003
+3074,Binary classification,Logistic regression,Bananas,0.5403383214053351,0.22148760330578512,0.004240989685058594,29.124189
+3180,Binary classification,Logistic regression,Bananas,0.5437106918238994,0.22031166039763567,0.004240989685058594,31.016333000000003
+3286,Binary classification,Logistic regression,Bananas,0.5450395617772368,0.21604614577871,0.004240989685058594,32.984057
+3392,Binary classification,Logistic regression,Bananas,0.5439268867924528,0.21272264631043258,0.004240989685058594,35.003757
+3498,Binary classification,Logistic regression,Bananas,0.5457404230989137,0.20827105132037868,0.004240989685058594,37.068178
+3604,Binary classification,Logistic regression,Bananas,0.5480022197558269,0.2042012701514411,0.004240989685058594,39.232173
+3710,Binary classification,Logistic regression,Bananas,0.546900269541779,0.19914244878513576,0.004240989685058594,41.450117000000006
+3816,Binary classification,Logistic regression,Bananas,0.5463836477987422,0.19450907398790138,0.004240989685058594,43.72876300000001
+3922,Binary classification,Logistic regression,Bananas,0.5474247832738399,0.1906064751481988,0.004240989685058594,46.072390000000006
+4028,Binary classification,Logistic regression,Bananas,0.547914597815293,0.1866904868244752,0.004240989685058594,48.42327300000001
+4134,Binary classification,Logistic regression,Bananas,0.548137397194001,0.18285214348206474,0.004240989685058594,50.870554000000006
+4240,Binary classification,Logistic regression,Bananas,0.5474056603773585,0.17886178861788615,0.004240989685058594,53.39424700000001
+4346,Binary classification,Logistic regression,Bananas,0.5476300046019328,0.17671691792294805,0.004240989685058594,55.939767
+4452,Binary classification,Logistic regression,Bananas,0.5498652291105122,0.1820408163265306,0.004240989685058594,58.584779000000005
+4558,Binary classification,Logistic regression,Bananas,0.5467310223782361,0.1814580031695721,0.004240989685058594,61.26661800000001
+4664,Binary classification,Logistic regression,Bananas,0.5465265866209262,0.18809980806142035,0.004240989685058594,64.04445700000001
+4770,Binary classification,Logistic regression,Bananas,0.5467505241090147,0.19086826347305388,0.004240989685058594,66.91140200000001
+4876,Binary classification,Logistic regression,Bananas,0.5469647251845775,0.19113877700476017,0.004240989685058594,69.84398600000002
+4982,Binary classification,Logistic regression,Bananas,0.5469690887193898,0.19765375044436545,0.004240989685058594,72.84582100000002
+5088,Binary classification,Logistic regression,Bananas,0.5448113207547169,0.19583333333333333,0.004240989685058594,75.85667200000002
+5194,Binary classification,Logistic regression,Bananas,0.5429341547939931,0.19416157501697218,0.004240989685058594,78.94956300000001
+5300,Binary classification,Logistic regression,Bananas,0.5432075471698113,0.1970149253731343,0.004240989685058594,82.06889500000001
+906,Binary classification,Logistic regression,Elec2,0.7980132450331126,0.7834319526627219,0.0053730010986328125,0.687155
+1812,Binary classification,Logistic regression,Elec2,0.8134657836644592,0.7488855869242199,0.0053730010986328125,2.092465
+2718,Binary classification,Logistic regression,Elec2,0.8024282560706402,0.7300150829562596,0.0053730010986328125,4.064074
+3624,Binary classification,Logistic regression,Elec2,0.8192604856512141,0.7598093142647598,0.0053730010986328125,6.824807
+4530,Binary classification,Logistic regression,Elec2,0.8289183222958058,0.7613181398213735,0.0053730010986328125,10.234028
+5436,Binary classification,Logistic regression,Elec2,0.8226637233259749,0.7528205128205128,0.0053730010986328125,14.344314
+6342,Binary classification,Logistic regression,Elec2,0.8229265216020183,0.7589611504614724,0.0053730010986328125,19.167838
+7248,Binary classification,Logistic regression,Elec2,0.8261589403973509,0.7617246596066566,0.0053730010986328125,24.744494
+8154,Binary classification,Logistic regression,Elec2,0.8318616629874908,0.7833096254148886,0.0053730010986328125,31.081721
+9060,Binary classification,Logistic regression,Elec2,0.8375275938189846,0.7975797579757975,0.0053730010986328125,38.163875000000004
+9966,Binary classification,Logistic regression,Elec2,0.8377483443708609,0.802008081302804,0.0053730010986328125,45.915004
+10872,Binary classification,Logistic regression,Elec2,0.8400478292862399,0.8089220964729151,0.0053730010986328125,54.352834
+11778,Binary classification,Logistic regression,Elec2,0.8432671081677704,0.8127789046653143,0.0053730010986328125,63.489549000000004
+12684,Binary classification,Logistic regression,Elec2,0.8419268369599495,0.8117547648108159,0.0053730010986328125,73.399178
+13590,Binary classification,Logistic regression,Elec2,0.8437821927888153,0.8167141500474834,0.0053730010986328125,84.03825400000001
+14496,Binary classification,Logistic regression,Elec2,0.8447157836644592,0.8189204408334004,0.0053730010986328125,95.41495900000001
+15402,Binary classification,Logistic regression,Elec2,0.8464485131801065,0.8201110519510155,0.0053730010986328125,107.55183300000002
+16308,Binary classification,Logistic regression,Elec2,0.8411822418444935,0.812780106982796,0.0053730010986328125,120.38661500000002
+17214,Binary classification,Logistic regression,Elec2,0.8397234808876496,0.8069954529555788,0.0053730010986328125,133.99787400000002
+18120,Binary classification,Logistic regression,Elec2,0.8419426048565122,0.80987785448752,0.0053730010986328125,148.356557
+19026,Binary classification,Logistic regression,Elec2,0.8451066961000736,0.8115849370244869,0.0053730010986328125,163.518734
+19932,Binary classification,Logistic regression,Elec2,0.8428155729480232,0.8097637986520129,0.0053730010986328125,179.395561
+20838,Binary classification,Logistic regression,Elec2,0.8393799788847298,0.805689404934688,0.0053730010986328125,196.009478
+21744,Binary classification,Logistic regression,Elec2,0.8402777777777778,0.8036632935722765,0.0053730010986328125,213.342445
+22650,Binary classification,Logistic regression,Elec2,0.8394701986754967,0.8009198423127463,0.0053730010986328125,231.348647
+23556,Binary classification,Logistic regression,Elec2,0.8357106469689252,0.7954545454545454,0.0053730010986328125,250.064916
+24462,Binary classification,Logistic regression,Elec2,0.8330471752105306,0.791441119395363,0.0053730010986328125,269.489469
+25368,Binary classification,Logistic regression,Elec2,0.8298249763481551,0.7872875092387287,0.0053730010986328125,289.628629
+26274,Binary classification,Logistic regression,Elec2,0.8304407398949532,0.787745962170661,0.0053730010986328125,310.508458
+27180,Binary classification,Logistic regression,Elec2,0.8308682855040471,0.7889638709085066,0.0053730010986328125,332.12320800000003
+28086,Binary classification,Logistic regression,Elec2,0.8277077547532579,0.7843678980437593,0.0053730010986328125,354.49968
+28992,Binary classification,Logistic regression,Elec2,0.8270212472406181,0.7820039121930016,0.0053730010986328125,377.655941
+29898,Binary classification,Logistic regression,Elec2,0.8260418757107498,0.780872129766168,0.0053730010986328125,401.520333
+30804,Binary classification,Logistic regression,Elec2,0.8258992338657317,0.7797807251673304,0.0053730010986328125,426.09085
+31710,Binary classification,Logistic regression,Elec2,0.821286660359508,0.7731294287201249,0.0053730010986328125,451.387139
+32616,Binary classification,Logistic regression,Elec2,0.8188619082658818,0.7700093428838368,0.0053730010986328125,477.46355
+33522,Binary classification,Logistic regression,Elec2,0.8168963665652408,0.7682024169184289,0.0053730010986328125,504.189667
+34428,Binary classification,Logistic regression,Elec2,0.8143952596723597,0.7647795037915042,0.0053730010986328125,531.635688
+35334,Binary classification,Logistic regression,Elec2,0.8142016188373804,0.7627822944896115,0.0053730010986328125,559.807066
+36240,Binary classification,Logistic regression,Elec2,0.8154801324503311,0.7629984051036682,0.0053730010986328125,588.709839
+37146,Binary classification,Logistic regression,Elec2,0.815161794002046,0.7614481273017858,0.0053730010986328125,618.344034
+38052,Binary classification,Logistic regression,Elec2,0.8151476926311363,0.7609596955073744,0.0053730010986328125,648.6306599999999
+38958,Binary classification,Logistic regression,Elec2,0.8162379998973254,0.7631274195149389,0.0053730010986328125,679.6980239999999
+39864,Binary classification,Logistic regression,Elec2,0.8169275536825206,0.7661946562439931,0.0053730010986328125,711.4719719999999
+40770,Binary classification,Logistic regression,Elec2,0.8186656855531028,0.7707241432780277,0.0053730010986328125,743.966698
+41676,Binary classification,Logistic regression,Elec2,0.8201602840963624,0.7745390006918749,0.0053730010986328125,777.181242
+42582,Binary classification,Logistic regression,Elec2,0.8211920529801324,0.7763613934089174,0.0053730010986328125,811.063029
+43488,Binary classification,Logistic regression,Elec2,0.8216979396615158,0.7772863051470587,0.0053730010986328125,845.685827
+44394,Binary classification,Logistic regression,Elec2,0.8211695274136145,0.7754109027129481,0.0053730010986328125,881.122534
+45300,Binary classification,Logistic regression,Elec2,0.8221412803532009,0.7771292633675417,0.0053730010986328125,917.330239
+45312,Binary classification,Logistic regression,Elec2,0.8221442443502824,0.7770862722319033,0.0053730010986328125,953.539999
+25,Binary classification,Logistic regression,Phishing,0.6,0.6428571428571429,0.005324363708496094,0.005087
+50,Binary classification,Logistic regression,Phishing,0.76,0.7499999999999999,0.005324363708496094,0.014273000000000001
+75,Binary classification,Logistic regression,Phishing,0.8,0.8,0.005324363708496094,0.080154
+100,Binary classification,Logistic regression,Phishing,0.81,0.8041237113402061,0.005324363708496094,0.160529
+125,Binary classification,Logistic regression,Phishing,0.8,0.7933884297520661,0.005324363708496094,0.244823
+150,Binary classification,Logistic regression,Phishing,0.8066666666666666,0.8079470198675497,0.005324363708496094,0.373717
+175,Binary classification,Logistic regression,Phishing,0.8171428571428572,0.8072289156626506,0.005324363708496094,0.564558
+200,Binary classification,Logistic regression,Phishing,0.815,0.8042328042328043,0.005324363708496094,0.765703
+225,Binary classification,Logistic regression,Phishing,0.8133333333333334,0.7980769230769231,0.005324363708496094,0.969796
+250,Binary classification,Logistic regression,Phishing,0.82,0.8068669527896996,0.005324363708496094,1.176844
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+400,Binary classification,Logistic regression,Phishing,0.85,0.8214285714285715,0.005564689636230469,2.973623
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+500,Binary classification,Logistic regression,Phishing,0.858,0.8297362110311751,0.005564689636230469,4.631479
+525,Binary classification,Logistic regression,Phishing,0.8571428571428571,0.8251748251748252,0.005564689636230469,5.084116
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+775,Binary classification,Logistic regression,Phishing,0.88,0.8549141965678626,0.005564689636230469,11.153806
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+1000,Binary classification,Logistic regression,Phishing,0.887,0.8675263774912075,0.005564689636230469,18.72316
+1025,Binary classification,Logistic regression,Phishing,0.8868292682926829,0.8678815489749431,0.005564689636230469,19.680949
+1050,Binary classification,Logistic regression,Phishing,0.8885714285714286,0.8704318936877077,0.005564689636230469,20.642059
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+1150,Binary classification,Logistic regression,Phishing,0.8895652173913043,0.8738828202581926,0.005564689636230469,24.78868
+1175,Binary classification,Logistic regression,Phishing,0.8885106382978724,0.872444011684518,0.005564689636230469,25.864657
+1200,Binary classification,Logistic regression,Phishing,0.8891666666666667,0.8729703915950333,0.005564689636230469,26.968066
+1225,Binary classification,Logistic regression,Phishing,0.889795918367347,0.8737137511693172,0.005564689636230469,28.075126
+1250,Binary classification,Logistic regression,Phishing,0.8872,0.8712328767123287,0.005564689636230469,29.206647
+1903,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,1.174944
+3806,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,3.465965
+5709,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,6.937403
+7612,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,11.610183
+9515,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,17.462392
+11418,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,24.519273000000002
+13321,Binary classification,Logistic regression,SMTP,1.0,0.0,0.004383087158203125,32.784706
+15224,Binary classification,Logistic regression,SMTP,0.9996715712033631,0.7058823529411764,0.004383087158203125,42.234241
+17127,Binary classification,Logistic regression,SMTP,0.9997080632918783,0.761904761904762,0.004383087158203125,52.882453
+19030,Binary classification,Logistic regression,SMTP,0.9997372569626904,0.761904761904762,0.004383087158203125,64.622668
+20933,Binary classification,Logistic regression,SMTP,0.999761142693355,0.761904761904762,0.004383087158203125,77.568109
+22836,Binary classification,Logistic regression,SMTP,0.9997810474689087,0.761904761904762,0.004383087158203125,91.771967
+24739,Binary classification,Logistic regression,SMTP,0.9997978899713004,0.761904761904762,0.004383087158203125,107.109486
+26642,Binary classification,Logistic regression,SMTP,0.9997747916823061,0.7272727272727273,0.004383087158203125,123.68183400000001
+28545,Binary classification,Logistic regression,SMTP,0.9997898055701524,0.7272727272727273,0.004383087158203125,141.369945
+30448,Binary classification,Logistic regression,SMTP,0.9998029427220179,0.7272727272727273,0.004383087158203125,160.23044
+32351,Binary classification,Logistic regression,SMTP,0.999814534326605,0.7272727272727273,0.004383087158203125,180.23963199999997
+34254,Binary classification,Logistic regression,SMTP,0.999824837975127,0.7272727272727273,0.004383087158203125,201.31894799999998
+36157,Binary classification,Logistic regression,SMTP,0.9998340570290677,0.7272727272727273,0.004383087158203125,223.51927299999997
+38060,Binary classification,Logistic regression,SMTP,0.9998423541776142,0.7272727272727273,0.004383087158203125,246.97671399999996
+39963,Binary classification,Logistic regression,SMTP,0.9998498611215374,0.7272727272727273,0.004383087158203125,271.56812399999995
+41866,Binary classification,Logistic regression,SMTP,0.999856685616013,0.7272727272727273,0.004383087158203125,297.29584399999993
+43769,Binary classification,Logistic regression,SMTP,0.9998629166761863,0.7272727272727273,0.004383087158203125,324.2115329999999
+45672,Binary classification,Logistic regression,SMTP,0.9998686284813453,0.7272727272727273,0.004383087158203125,352.27523699999995
+47575,Binary classification,Logistic regression,SMTP,0.9998738833420915,0.7272727272727273,0.004383087158203125,381.59710399999994
+49478,Binary classification,Logistic regression,SMTP,0.9998787339827803,0.7272727272727273,0.004383087158203125,412.11662699999994
+51381,Binary classification,Logistic regression,SMTP,0.9998443004223351,0.6666666666666666,0.004383087158203125,443.86742899999996
+53284,Binary classification,Logistic regression,SMTP,0.9998498611215374,0.6666666666666666,0.004383087158203125,476.83879799999994
+55187,Binary classification,Logistic regression,SMTP,0.999855038324243,0.6666666666666666,0.004383087158203125,510.9819989999999
+57090,Binary classification,Logistic regression,SMTP,0.9997022245577158,0.48484848484848486,0.004383087158203125,546.274013
+58993,Binary classification,Logistic regression,SMTP,0.9997118302171444,0.48484848484848486,0.004383087158203125,582.6678519999999
+60896,Binary classification,Logistic regression,SMTP,0.9997208355228586,0.48484848484848486,0.004383087158203125,620.2082039999999
+62799,Binary classification,Logistic regression,SMTP,0.999697447411583,0.45714285714285713,0.004383087158203125,658.8625569999999
+64702,Binary classification,Logistic regression,SMTP,0.9997063460171247,0.45714285714285713,0.004383087158203125,698.5852799999999
+66605,Binary classification,Logistic regression,SMTP,0.9997147361309211,0.45714285714285713,0.004383087158203125,739.3620329999999
+68508,Binary classification,Logistic regression,SMTP,0.9996934664564723,0.4324324324324324,0.004383087158203125,781.2563779999999
+70411,Binary classification,Logistic regression,SMTP,0.9997017511468379,0.4324324324324324,0.004383087158203125,824.198222
+72314,Binary classification,Logistic regression,SMTP,0.9997095998008685,0.4324324324324324,0.004383087158203125,868.202086
+74217,Binary classification,Logistic regression,SMTP,0.9997170459598205,0.4324324324324324,0.004383087158203125,913.268811
+76120,Binary classification,Logistic regression,SMTP,0.999724119810825,0.4324324324324324,0.004383087158203125,959.4161730000001
+78023,Binary classification,Logistic regression,SMTP,0.9997308485959269,0.4324324324324324,0.004383087158203125,1006.608919
+79926,Binary classification,Logistic regression,SMTP,0.9997372569626904,0.4324324324324324,0.004383087158203125,1054.8516300000001
+81829,Binary classification,Logistic regression,SMTP,0.9997433672658838,0.4324324324324324,0.004383087158203125,1104.06085
+83732,Binary classification,Logistic regression,SMTP,0.9997491998280228,0.4324324324324324,0.004383087158203125,1154.258062
+85635,Binary classification,Logistic regression,SMTP,0.9997547731651778,0.4324324324324324,0.004383087158203125,1205.3715320000001
+87538,Binary classification,Logistic regression,SMTP,0.9997601041833261,0.4324324324324324,0.004383087158203125,1257.4462130000002
+89441,Binary classification,Logistic regression,SMTP,0.9997540277948592,0.4210526315789474,0.004383087158203125,1310.5048250000002
+91344,Binary classification,Logistic regression,SMTP,0.9997591522157996,0.4210526315789474,0.004383087158203125,1364.5437910000003
+93247,Binary classification,Logistic regression,SMTP,0.9997640674767017,0.4210526315789474,0.004383087158203125,1419.4942320000002
+95150,Binary classification,Logistic regression,SMTP,0.9997687861271676,0.4210526315789474,0.004383087158203125,1475.4318390000003
+95156,Binary classification,Logistic regression,SMTP,0.9997688007062088,0.4210526315789474,0.004383087158203125,1531.3705140000004
+106,Binary classification,Aggregated Mondrian Forest,Bananas,0.7047619047619048,0.6990291262135924,0.8133068084716797,0.833499
+212,Binary classification,Aggregated Mondrian Forest,Bananas,0.7867298578199052,0.7668393782383419,1.3378009796142578,2.8663
+318,Binary classification,Aggregated Mondrian Forest,Bananas,0.8233438485804416,0.806896551724138,1.855398178100586,6.250927
+424,Binary classification,Aggregated Mondrian Forest,Bananas,0.8392434988179669,0.8229166666666667,2.3226680755615234,11.143336
+530,Binary classification,Aggregated Mondrian Forest,Bananas,0.8412098298676749,0.8181818181818182,2.776212692260742,17.797124
+636,Binary classification,Aggregated Mondrian Forest,Bananas,0.8488188976377953,0.8267148014440434,3.173288345336914,26.396562
+742,Binary classification,Aggregated Mondrian Forest,Bananas,0.8596491228070176,0.8359621451104102,3.5500621795654297,36.969223
+848,Binary classification,Aggregated Mondrian Forest,Bananas,0.8677685950413223,0.8461538461538461,3.917997360229492,49.692848
+954,Binary classification,Aggregated Mondrian Forest,Bananas,0.8730325288562435,0.8515337423312884,4.238534927368164,64.631677
+1060,Binary classification,Aggregated Mondrian Forest,Bananas,0.8772426817752597,0.8549107142857144,4.491437911987305,81.765253
+1166,Binary classification,Aggregated Mondrian Forest,Bananas,0.8772532188841202,0.8557013118062564,4.809717178344727,101.295253
+1272,Binary classification,Aggregated Mondrian Forest,Bananas,0.8772619984264359,0.8566176470588236,5.171953201293945,123.161687
+1378,Binary classification,Aggregated Mondrian Forest,Bananas,0.8779956427015251,0.8561643835616438,5.501619338989258,147.513883
+1484,Binary classification,Aggregated Mondrian Forest,Bananas,0.8813216453135536,0.860759493670886,5.80189323425293,174.53874199999998
+1590,Binary classification,Aggregated Mondrian Forest,Bananas,0.8785399622404028,0.8579838116261957,6.17225456237793,204.250002
+1696,Binary classification,Aggregated Mondrian Forest,Bananas,0.8790560471976401,0.8585231193926847,6.45002555847168,237.091398
+1802,Binary classification,Aggregated Mondrian Forest,Bananas,0.8806218767351471,0.8613797549967763,6.703157424926758,272.83416
+1908,Binary classification,Aggregated Mondrian Forest,Bananas,0.8783429470372313,0.8602409638554217,7.075212478637695,311.419605
+2014,Binary classification,Aggregated Mondrian Forest,Bananas,0.8777943368107303,0.8607021517553795,7.409914016723633,352.79492
+2120,Binary classification,Aggregated Mondrian Forest,Bananas,0.8791882963662104,0.8636847710330138,7.730207443237305,397.065386
+2226,Binary classification,Aggregated Mondrian Forest,Bananas,0.8782022471910113,0.8626457171819564,8.068941116333008,444.302777
+2332,Binary classification,Aggregated Mondrian Forest,Bananas,0.8777348777348777,0.8621190130624092,8.392999649047852,494.454577
+2438,Binary classification,Aggregated Mondrian Forest,Bananas,0.8781288469429627,0.8624363131079205,8.738908767700195,547.433225
+2544,Binary classification,Aggregated Mondrian Forest,Bananas,0.8784899724734565,0.8635761589403974,9.069158554077148,603.367304
+2650,Binary classification,Aggregated Mondrian Forest,Bananas,0.8799546998867497,0.8654822335025381,9.380228042602539,661.971994
+2756,Binary classification,Aggregated Mondrian Forest,Bananas,0.8820326678765881,0.8676171079429736,9.675683975219727,723.088894
+2862,Binary classification,Aggregated Mondrian Forest,Bananas,0.8836071303739951,0.86905230043256,10.005556106567383,786.780009
+2968,Binary classification,Aggregated Mondrian Forest,Bananas,0.8840579710144928,0.8691019786910198,10.283010482788086,853.0146269999999
+3074,Binary classification,Aggregated Mondrian Forest,Bananas,0.8831760494630654,0.8683535020168683,10.632661819458008,921.6671329999999
+3180,Binary classification,Aggregated Mondrian Forest,Bananas,0.8858131487889274,0.8707725169099323,10.90281867980957,992.810764
+3286,Binary classification,Aggregated Mondrian Forest,Bananas,0.8852359208523592,0.8696854476322157,11.200468063354492,1066.389204
+3392,Binary classification,Aggregated Mondrian Forest,Bananas,0.8849896785608965,0.87017310252996,11.512235641479492,1142.442462
+3498,Binary classification,Aggregated Mondrian Forest,Bananas,0.8864741206748642,0.8712293220888745,11.797895431518555,1221.036812
+3604,Binary classification,Aggregated Mondrian Forest,Bananas,0.8878712184290869,0.8721518987341771,12.102933883666992,1302.125963
+3710,Binary classification,Aggregated Mondrian Forest,Bananas,0.8878403882448099,0.8725490196078431,12.41331672668457,1385.838182
+3816,Binary classification,Aggregated Mondrian Forest,Bananas,0.889646133682831,0.8746650788925276,12.665735244750977,1472.135343
+3922,Binary classification,Aggregated Mondrian Forest,Bananas,0.8885488395817394,0.8730758059831543,13.002767562866211,1561.047711
+4028,Binary classification,Aggregated Mondrian Forest,Bananas,0.8872609883287808,0.8714609286523215,13.407987594604492,1652.580672
+4134,Binary classification,Aggregated Mondrian Forest,Bananas,0.8874909266876361,0.8717241379310345,13.751871109008789,1746.8148660000002
+4240,Binary classification,Aggregated Mondrian Forest,Bananas,0.8886529841943854,0.8731864588930682,13.96497917175293,1843.750561
+4346,Binary classification,Aggregated Mondrian Forest,Bananas,0.8895281933256617,0.8742138364779874,14.240518569946289,1943.4032140000002
+4452,Binary classification,Aggregated Mondrian Forest,Bananas,0.8890137047854415,0.8735926305015352,14.605810165405273,2045.776976
+4558,Binary classification,Aggregated Mondrian Forest,Bananas,0.8894009216589862,0.874439461883408,14.917993545532227,2150.6554650000003
+4664,Binary classification,Aggregated Mondrian Forest,Bananas,0.8893416255629423,0.8748180494905387,15.239774703979492,2258.064088
+4770,Binary classification,Aggregated Mondrian Forest,Bananas,0.8880268400083875,0.8729176582579724,15.676980972290039,2367.913167
+4876,Binary classification,Aggregated Mondrian Forest,Bananas,0.8888205128205128,0.8733644859813083,15.964864730834961,2480.267593
+4982,Binary classification,Aggregated Mondrian Forest,Bananas,0.889580405541056,0.8746010031919745,16.210702896118164,2595.134509
+5088,Binary classification,Aggregated Mondrian Forest,Bananas,0.8891291527422842,0.8740509155873157,16.543100357055664,2712.434229
+5194,Binary classification,Aggregated Mondrian Forest,Bananas,0.8894665896398999,0.8743982494529539,16.87101936340332,2832.294496
+5300,Binary classification,Aggregated Mondrian Forest,Bananas,0.889413096810719,0.8742489270386266,17.23769187927246,2954.746773
+906,Binary classification,Aggregated Mondrian Forest,Elec2,0.8662983425414365,0.8638920134983127,5.093213081359863,9.961559
+1812,Binary classification,Aggregated Mondrian Forest,Elec2,0.8895637769188294,0.863013698630137,9.274415016174316,34.997891
+2718,Binary classification,Aggregated Mondrian Forest,Elec2,0.8737578211262422,0.8433074463225217,14.81954288482666,77.180768
+3624,Binary classification,Aggregated Mondrian Forest,Elec2,0.8746894838531604,0.8451568894952252,20.35789203643799,135.799753
+4530,Binary classification,Aggregated Mondrian Forest,Elec2,0.869728416869066,0.8295782784517621,25.320820808410645,209.04868100000002
+5436,Binary classification,Aggregated Mondrian Forest,Elec2,0.8658693652253909,0.8254728273880776,30.942105293273926,297.509476
+6342,Binary classification,Aggregated Mondrian Forest,Elec2,0.8613783314934553,0.8220287507592631,36.922226905822754,401.254404
+7248,Binary classification,Aggregated Mondrian Forest,Elec2,0.8563543535255967,0.8144715736945286,42.8322229385376,518.853069
+8154,Binary classification,Aggregated Mondrian Forest,Elec2,0.8547773825585674,0.8211480362537765,49.13461780548096,650.61595
+9060,Binary classification,Aggregated Mondrian Forest,Elec2,0.8564963020200905,0.8276776246023331,54.274807929992676,797.031608
+9966,Binary classification,Aggregated Mondrian Forest,Elec2,0.8559959859508279,0.830478440637921,59.58850955963135,957.298151
+10872,Binary classification,Aggregated Mondrian Forest,Elec2,0.858522675006899,0.8360690684289065,64.43849277496338,1132.655012
+11778,Binary classification,Aggregated Mondrian Forest,Elec2,0.8588774730406725,0.8365138697619515,69.77676105499268,1321.3849659999998
+12684,Binary classification,Aggregated Mondrian Forest,Elec2,0.8572892848695104,0.8352148579752368,75.08023929595947,1522.7749099999999
+13590,Binary classification,Aggregated Mondrian Forest,Elec2,0.8577525940098609,0.8380665158750105,79.94311618804932,1737.8701859999999
+14496,Binary classification,Aggregated Mondrian Forest,Elec2,0.8584339427388755,0.8393863494051347,84.43613529205322,1968.1055499999998
+15402,Binary classification,Aggregated Mondrian Forest,Elec2,0.8584507499513019,0.8387335404645658,89.24470615386963,2211.4324739999997
+16308,Binary classification,Aggregated Mondrian Forest,Elec2,0.8561354019746121,0.8352296670880741,95.65516376495361,2468.910492
+17214,Binary classification,Aggregated Mondrian Forest,Elec2,0.8563295183872655,0.8333445649976414,100.85075855255127,2740.76049
+18120,Binary classification,Aggregated Mondrian Forest,Elec2,0.8570009382416248,0.834176,106.8406229019165,3026.823297
+19026,Binary classification,Aggregated Mondrian Forest,Elec2,0.858712220762155,0.8348082595870207,111.74584293365479,3325.548438
+19932,Binary classification,Aggregated Mondrian Forest,Elec2,0.8587125583262255,0.8363361618040218,117.02025699615479,3636.553219
+20838,Binary classification,Aggregated Mondrian Forest,Elec2,0.8564572635216202,0.8339348176114596,123.37252902984619,3960.554229
+21744,Binary classification,Aggregated Mondrian Forest,Elec2,0.8540219840868325,0.8286917098445596,130.42929553985596,4298.210438
+22650,Binary classification,Aggregated Mondrian Forest,Elec2,0.8531944015188309,0.8264160793526494,136.64212131500244,4650.500753
+23556,Binary classification,Aggregated Mondrian Forest,Elec2,0.8528550201655699,0.8255134917438581,142.6701021194458,5016.675492
+24462,Binary classification,Aggregated Mondrian Forest,Elec2,0.8532766444544376,0.8247130647130647,148.4442949295044,5397.142957
+25368,Binary classification,Aggregated Mondrian Forest,Elec2,0.8514605589939686,0.8225487425826504,154.72937488555908,5792.939295
+26274,Binary classification,Aggregated Mondrian Forest,Elec2,0.8521676245575306,0.8231490756761678,160.280930519104,6204.791143
+27180,Binary classification,Aggregated Mondrian Forest,Elec2,0.8530851024688179,0.8247069669432372,165.12001132965088,6630.671498000001
+28086,Binary classification,Aggregated Mondrian Forest,Elec2,0.8528752002848495,0.8239904583404327,171.1938066482544,7068.974646000001
+28992,Binary classification,Aggregated Mondrian Forest,Elec2,0.8532303128557138,0.8236415633937083,176.66365909576416,7519.88705
+29898,Binary classification,Aggregated Mondrian Forest,Elec2,0.8538649362812323,0.8241355713883187,181.78493976593018,7981.8746790000005
+30804,Binary classification,Aggregated Mondrian Forest,Elec2,0.8542349771126189,0.8238110186783865,187.08849048614502,8454.454599
+31710,Binary classification,Aggregated Mondrian Forest,Elec2,0.8525655176763695,0.8216125462662648,193.5201120376587,8938.242097
+32616,Binary classification,Aggregated Mondrian Forest,Elec2,0.852245899126169,0.821432541594101,199.6366205215454,9433.534304
+33522,Binary classification,Aggregated Mondrian Forest,Elec2,0.852003221860923,0.8214247147330909,205.81115818023682,9940.639789
+34428,Binary classification,Aggregated Mondrian Forest,Elec2,0.851715223516426,0.8209965286300361,212.10033893585205,10459.964952
+35334,Binary classification,Aggregated Mondrian Forest,Elec2,0.8513287861206238,0.8197137660019906,218.64550113677979,10993.026606
+36240,Binary classification,Aggregated Mondrian Forest,Elec2,0.8508788873865173,0.8179735920237133,225.19258975982666,11538.003928999999
+37146,Binary classification,Aggregated Mondrian Forest,Elec2,0.8496432898102032,0.8159741671883752,232.33557987213135,12096.169426999999
+38052,Binary classification,Aggregated Mondrian Forest,Elec2,0.8497279966360937,0.8155126798735239,238.56606006622314,12664.877691
+38958,Binary classification,Aggregated Mondrian Forest,Elec2,0.8494493929203994,0.8154906093686098,244.89648151397705,13243.508414
+39864,Binary classification,Aggregated Mondrian Forest,Elec2,0.8492336251661942,0.8164773421277635,251.12543201446533,13830.859859
+40770,Binary classification,Aggregated Mondrian Forest,Elec2,0.8486104638328141,0.8170174918470204,257.83575916290283,14427.278119
+41676,Binary classification,Aggregated Mondrian Forest,Elec2,0.8490941811637672,0.8186928820595613,264.1331262588501,15032.883602
+42582,Binary classification,Aggregated Mondrian Forest,Elec2,0.8493929217256523,0.8194385787087872,270.1314744949341,15648.679676
+43488,Binary classification,Aggregated Mondrian Forest,Elec2,0.8493802745648125,0.8194995590828924,276.04683017730713,16273.986894
+44394,Binary classification,Aggregated Mondrian Forest,Elec2,0.8493681436262474,0.8189620164063134,282.1419038772583,16909.074578
+45300,Binary classification,Aggregated Mondrian Forest,Elec2,0.8499083864985982,0.8197651300267741,287.208477973938,17554.066457
+45312,Binary classification,Aggregated Mondrian Forest,Elec2,0.8499039968219637,0.8197312269727252,287.3145227432251,18206.640571
+25,Binary classification,Aggregated Mondrian Forest,Phishing,0.6666666666666666,0.6923076923076924,0.2663440704345703,0.180038
+50,Binary classification,Aggregated Mondrian Forest,Phishing,0.7755102040816326,0.7555555555555555,0.40291404724121094,0.591649
+75,Binary classification,Aggregated Mondrian Forest,Phishing,0.7972972972972973,0.7945205479452055,0.5196552276611328,1.2897159999999999
+100,Binary classification,Aggregated Mondrian Forest,Phishing,0.8181818181818182,0.8125,0.6383838653564453,2.331468
+125,Binary classification,Aggregated Mondrian Forest,Phishing,0.8225806451612904,0.819672131147541,0.7669887542724609,3.7241540000000004
+150,Binary classification,Aggregated Mondrian Forest,Phishing,0.8456375838926175,0.847682119205298,0.9175167083740234,5.520175
+175,Binary classification,Aggregated Mondrian Forest,Phishing,0.867816091954023,0.8606060606060606,1.0086803436279297,7.7498439999999995
+200,Binary classification,Aggregated Mondrian Forest,Phishing,0.864321608040201,0.8571428571428572,1.1245098114013672,10.53336
+225,Binary classification,Aggregated Mondrian Forest,Phishing,0.8660714285714286,0.8557692307692308,1.2114391326904297,13.795268
+250,Binary classification,Aggregated Mondrian Forest,Phishing,0.8554216867469879,0.8448275862068965,1.322244644165039,17.57486
+275,Binary classification,Aggregated Mondrian Forest,Phishing,0.8540145985401459,0.84251968503937,1.3987751007080078,21.876977
+300,Binary classification,Aggregated Mondrian Forest,Phishing,0.8561872909698997,0.8413284132841329,1.489828109741211,26.743447
+325,Binary classification,Aggregated Mondrian Forest,Phishing,0.8672839506172839,0.8501742160278746,1.5769939422607422,32.2729
+350,Binary classification,Aggregated Mondrian Forest,Phishing,0.8681948424068768,0.8486842105263156,1.638784408569336,38.477964
+375,Binary classification,Aggregated Mondrian Forest,Phishing,0.8689839572192514,0.8482972136222912,1.7178211212158203,45.357054
+400,Binary classification,Aggregated Mondrian Forest,Phishing,0.8671679197994987,0.8436578171091446,1.7941875457763672,52.888585
+425,Binary classification,Aggregated Mondrian Forest,Phishing,0.8702830188679245,0.8433048433048433,1.8353633880615234,61.095765
+450,Binary classification,Aggregated Mondrian Forest,Phishing,0.8730512249443207,0.8455284552845528,1.9096240997314453,70.024579
+475,Binary classification,Aggregated Mondrian Forest,Phishing,0.8755274261603375,0.8506329113924052,1.988790512084961,79.720297
+500,Binary classification,Aggregated Mondrian Forest,Phishing,0.875751503006012,0.8530805687203792,2.063833236694336,90.07863400000001
+525,Binary classification,Aggregated Mondrian Forest,Phishing,0.8778625954198473,0.8525345622119817,2.144712448120117,101.25810100000001
+550,Binary classification,Aggregated Mondrian Forest,Phishing,0.8779599271402551,0.8533916849015317,2.1996402740478516,113.25181900000001
+575,Binary classification,Aggregated Mondrian Forest,Phishing,0.8780487804878049,0.8535564853556484,2.2528209686279297,125.93584100000001
+600,Binary classification,Aggregated Mondrian Forest,Phishing,0.8797996661101837,0.8536585365853657,2.283121109008789,139.44840100000002
+625,Binary classification,Aggregated Mondrian Forest,Phishing,0.8814102564102564,0.852589641434263,2.343900680541992,153.77905700000002
+650,Binary classification,Aggregated Mondrian Forest,Phishing,0.884437596302003,0.8587570621468926,2.418844223022461,168.92061400000003
+675,Binary classification,Aggregated Mondrian Forest,Phishing,0.884272997032641,0.8617021276595745,2.468423843383789,184.94000100000002
+700,Binary classification,Aggregated Mondrian Forest,Phishing,0.8884120171673819,0.8650519031141869,2.478273391723633,201.76583000000002
+725,Binary classification,Aggregated Mondrian Forest,Phishing,0.8895027624309392,0.8684210526315789,2.5243663787841797,219.457713
+750,Binary classification,Aggregated Mondrian Forest,Phishing,0.8918558077436582,0.8716323296354993,2.5813236236572266,238.014124
+775,Binary classification,Aggregated Mondrian Forest,Phishing,0.8914728682170543,0.8707692307692307,2.6200389862060547,257.461391
+800,Binary classification,Aggregated Mondrian Forest,Phishing,0.8898623279098874,0.8702064896755163,2.657014846801758,277.779634
+825,Binary classification,Aggregated Mondrian Forest,Phishing,0.8907766990291263,0.872159090909091,2.706361770629883,298.980548
+850,Binary classification,Aggregated Mondrian Forest,Phishing,0.8928150765606596,0.8741355463347164,2.730466842651367,321.097396
+875,Binary classification,Aggregated Mondrian Forest,Phishing,0.8958810068649885,0.8771929824561403,2.7533512115478516,344.186724
+900,Binary classification,Aggregated Mondrian Forest,Phishing,0.8976640711902113,0.8786279683377309,2.807779312133789,368.101507
+925,Binary classification,Aggregated Mondrian Forest,Phishing,0.9004329004329005,0.8829516539440204,2.8523120880126953,392.98062400000003
+950,Binary classification,Aggregated Mondrian Forest,Phishing,0.9009483667017913,0.8850855745721271,2.913583755493164,418.83123200000006
+975,Binary classification,Aggregated Mondrian Forest,Phishing,0.9024640657084189,0.8867699642431467,2.943540573120117,445.63277700000003
+1000,Binary classification,Aggregated Mondrian Forest,Phishing,0.9009009009009009,0.8850174216027874,2.9903697967529297,473.39902800000004
+1025,Binary classification,Aggregated Mondrian Forest,Phishing,0.8994140625,0.8836158192090395,3.035707473754883,502.22467600000004
+1050,Binary classification,Aggregated Mondrian Forest,Phishing,0.9008579599618685,0.8857142857142858,3.069150924682617,532.049603
+1075,Binary classification,Aggregated Mondrian Forest,Phishing,0.9013035381750466,0.8869936034115138,3.114839553833008,562.838704
+1100,Binary classification,Aggregated Mondrian Forest,Phishing,0.9035486806187443,0.8898128898128899,3.132375717163086,594.67778
+1125,Binary classification,Aggregated Mondrian Forest,Phishing,0.905693950177936,0.8933601609657947,3.1889095306396484,627.518257
+1150,Binary classification,Aggregated Mondrian Forest,Phishing,0.9060052219321149,0.893491124260355,3.220029830932617,661.4048929999999
+1175,Binary classification,Aggregated Mondrian Forest,Phishing,0.9045996592844975,0.8916827852998066,3.270620346069336,696.4079739999999
+1200,Binary classification,Aggregated Mondrian Forest,Phishing,0.9040867389491243,0.8909952606635072,3.311410903930664,732.4743999999998
+1225,Binary classification,Aggregated Mondrian Forest,Phishing,0.9044117647058824,0.8911627906976743,3.344022750854492,769.4892029999999
+1250,Binary classification,Aggregated Mondrian Forest,Phishing,0.9047237790232185,0.8921124206708976,3.391061782836914,807.5726659999999
+1903,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,2.745403
+3806,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,8.183125
+5709,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,16.539666
+7612,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,27.755785000000003
+9515,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,41.777067
+11418,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,58.637769000000006
+13321,Binary classification,Aggregated Mondrian Forest,SMTP,1.0,0.0,0.04407501220703125,78.268206
+15224,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998686198515404,0.9090909090909091,0.09231853485107422,101.443914
+17127,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998832184981898,0.9230769230769231,0.09723186492919922,131.805417
+19030,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998948972620737,0.9230769230769231,0.09728145599365234,169.246217
+20933,Binary classification,Aggregated Mondrian Forest,SMTP,0.999904452512899,0.9230769230769231,0.09728145599365234,213.148727
+22836,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999124151521787,0.9230769230769231,0.09728145599365234,263.357684
+24739,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999191527205109,0.9230769230769231,0.09730815887451172,319.49775
+26642,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998873916144289,0.888888888888889,0.10914134979248047,381.401703
+28545,Binary classification,Aggregated Mondrian Forest,SMTP,0.999894899103139,0.888888888888889,0.10916423797607422,448.60874
+30448,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999014681249384,0.888888888888889,0.10916423797607422,520.91477
+32351,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999072642967543,0.888888888888889,0.10966777801513672,598.09858
+34254,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999124164306776,0.888888888888889,0.11131954193115234,680.064697
+36157,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999170262197146,0.888888888888889,0.11127376556396484,766.82968
+38060,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999211750177356,0.888888888888889,0.11127376556396484,858.2478070000001
+39963,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999249286822481,0.888888888888889,0.11127376556396484,954.233503
+41866,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999283410963812,0.888888888888889,0.11127376556396484,1054.7914
+43769,Binary classification,Aggregated Mondrian Forest,SMTP,0.999931456772071,0.888888888888889,0.11127376556396484,1159.6703400000001
+45672,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999343128024348,0.888888888888889,0.11127376556396484,1268.4432900000002
+47575,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999369403455669,0.888888888888889,0.1298818588256836,1381.2685860000001
+49478,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999393657659115,0.888888888888889,0.1299276351928711,1498.4984390000002
+51381,Binary classification,Aggregated Mondrian Forest,SMTP,0.999941611521993,0.9032258064516129,0.14348888397216797,1620.0599740000002
+53284,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999436968639153,0.9032258064516129,0.14348888397216797,1745.8256190000002
+55187,Binary classification,Aggregated Mondrian Forest,SMTP,0.9999456383865473,0.9032258064516129,0.14403820037841797,1875.6542580000003
+57090,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998248349068998,0.7619047619047621,0.1476888656616211,2010.2723030000002
+58993,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998304854895579,0.7619047619047621,0.15108394622802734,2149.2802330000004
+60896,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998357829050004,0.7619047619047621,0.1510610580444336,2292.3763450000006
+62799,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998089111118188,0.7272727272727272,0.15114116668701172,2439.4913830000005
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+66605,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998198306408024,0.7272727272727272,0.1576833724975586,2745.6113380000006
+68508,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998248354182784,0.75,0.1762075424194336,2905.2725530000007
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+74217,Binary classification,Aggregated Mondrian Forest,SMTP,0.9998383097984263,0.75,0.17613887786865234,3411.935267000001
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+3392,Binary classification,ALMA,Bananas,0.5103183962264151,0.49095923996322405,0.0029211044311523438,28.215584
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+3710,Binary classification,ALMA,Bananas,0.5118598382749326,0.49086308687095864,0.0029211044311523438,33.864206
+3816,Binary classification,ALMA,Bananas,0.510482180293501,0.4893384363039912,0.0029211044311523438,35.803291
+3922,Binary classification,ALMA,Bananas,0.50790413054564,0.48588172615876407,0.0029211044311523438,37.844614
+4028,Binary classification,ALMA,Bananas,0.506454816285998,0.48443983402489627,0.0029211044311523438,39.968017
+4134,Binary classification,ALMA,Bananas,0.5050798258345428,0.48281092012133464,0.0029211044311523438,42.128298
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+5300,Binary classification,ALMA,Bananas,0.5064150943396226,0.4825949367088608,0.0029211044311523438,68.97313600000001
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+11778,Binary classification,ALMA,Elec2,0.9313975208014943,0.9218568665377176,0.0043582916259765625,57.61408300000001
+12684,Binary classification,ALMA,Elec2,0.9290444654683065,0.9191665169750315,0.0043582916259765625,66.44160400000001
+13590,Binary classification,ALMA,Elec2,0.9298013245033112,0.9209872453205235,0.0043582916259765625,75.85703300000002
+14496,Binary classification,ALMA,Elec2,0.9305325607064018,0.9222213640225535,0.0043582916259765625,85.90938600000001
+15402,Binary classification,ALMA,Elec2,0.9308531359563693,0.922279792746114,0.0043582916259765625,96.62160000000002
+16308,Binary classification,ALMA,Elec2,0.9293598233995585,0.9203319502074688,0.0043582916259765625,107.96559300000001
+17214,Binary classification,ALMA,Elec2,0.9279656093877077,0.9176298658163943,0.0043582916259765625,119.98412300000001
+18120,Binary classification,ALMA,Elec2,0.9266004415011038,0.9160141449861076,0.0043582916259765625,132.63841200000002
+19026,Binary classification,ALMA,Elec2,0.9265741616734994,0.915143048047136,0.0043582916259765625,146.00166900000002
+19932,Binary classification,ALMA,Elec2,0.9262994180212724,0.9155892662184681,0.0043582916259765625,159.938555
+20838,Binary classification,ALMA,Elec2,0.9232171993473461,0.9122710823555213,0.0043582916259765625,174.54734100000002
+21744,Binary classification,ALMA,Elec2,0.9225073583517293,0.9101955977189149,0.0043582916259765625,189.73533200000003
+22650,Binary classification,ALMA,Elec2,0.9217218543046357,0.9087540528022233,0.0043582916259765625,205.61954500000002
+23556,Binary classification,ALMA,Elec2,0.9186619120393955,0.9050639183430779,0.0043582916259765625,222.16184900000002
+24462,Binary classification,ALMA,Elec2,0.9173003025100155,0.902885123133791,0.0043582916259765625,239.39901500000002
+25368,Binary classification,ALMA,Elec2,0.9144985808893094,0.8997643144322751,0.0043582916259765625,257.26822000000004
+26274,Binary classification,ALMA,Elec2,0.9142498287280201,0.8992622401073105,0.0043582916259765625,275.765482
+27180,Binary classification,ALMA,Elec2,0.9138337012509198,0.89909521757863,0.0043582916259765625,294.848784
+28086,Binary classification,ALMA,Elec2,0.9110232856227302,0.8955049132343716,0.0043582916259765625,314.617946
+28992,Binary classification,ALMA,Elec2,0.9101476269315674,0.8940927755417328,0.0043582916259765625,335.076303
+29898,Binary classification,ALMA,Elec2,0.9094922737306843,0.8931701539676272,0.0043582916259765625,356.063392
+30804,Binary classification,ALMA,Elec2,0.9083235943383976,0.8913093680240166,0.0043582916259765625,377.56682800000004
+31710,Binary classification,ALMA,Elec2,0.9062125512456638,0.8888722815933038,0.0043582916259765625,399.67833300000007
+32616,Binary classification,ALMA,Elec2,0.9052918812852587,0.8879294706671989,0.0043582916259765625,422.4669390000001
+33522,Binary classification,ALMA,Elec2,0.9050474315374978,0.8877050626212737,0.0043582916259765625,445.7904010000001
+34428,Binary classification,ALMA,Elec2,0.9050772626931567,0.8877901387172092,0.0043582916259765625,469.7481780000001
+35334,Binary classification,ALMA,Elec2,0.9045395369898681,0.8866104144955793,0.0043582916259765625,494.21097500000013
+36240,Binary classification,ALMA,Elec2,0.9048013245033113,0.8860483551327785,0.0043582916259765625,519.3392310000002
+37146,Binary classification,ALMA,Elec2,0.9045119259139611,0.8854217139903738,0.0043582916259765625,545.0643520000001
+38052,Binary classification,ALMA,Elec2,0.9042625880374224,0.8846092933388237,0.0043582916259765625,571.4397520000001
+38958,Binary classification,ALMA,Elec2,0.904409877303763,0.88502624266749,0.0043582916259765625,598.3711440000001
+39864,Binary classification,ALMA,Elec2,0.904926750953241,0.8863636363636365,0.0043582916259765625,626.0397580000001
+40770,Binary classification,ALMA,Elec2,0.9055187637969095,0.8878667908709827,0.0043582916259765625,654.3634580000002
+41676,Binary classification,ALMA,Elec2,0.9061090315769268,0.8892285916489738,0.0043582916259765625,683.2521370000002
+42582,Binary classification,ALMA,Elec2,0.9063923723639097,0.889810361032786,0.0043582916259765625,712.7682970000002
+43488,Binary classification,ALMA,Elec2,0.9067098969830758,0.8902534693104661,0.0043582916259765625,742.9022130000002
+44394,Binary classification,ALMA,Elec2,0.9062711177186106,0.8894732648019762,0.0043582916259765625,773.7300850000001
+45300,Binary classification,ALMA,Elec2,0.9064238410596026,0.8897844569823977,0.0043582916259765625,805.1132940000001
+45312,Binary classification,ALMA,Elec2,0.9064265536723164,0.8897670549084858,0.0043582916259765625,836.4982200000001
+25,Binary classification,ALMA,Phishing,0.56,0.5217391304347826,0.004366874694824219,0.003459
+50,Binary classification,ALMA,Phishing,0.7,0.6341463414634146,0.004366874694824219,0.050212
+75,Binary classification,ALMA,Phishing,0.7066666666666667,0.676470588235294,0.004366874694824219,0.100001
+100,Binary classification,ALMA,Phishing,0.72,0.702127659574468,0.004366874694824219,0.15312800000000001
+125,Binary classification,ALMA,Phishing,0.72,0.7058823529411765,0.004366874694824219,0.22806300000000002
+150,Binary classification,ALMA,Phishing,0.7133333333333334,0.7189542483660132,0.004366874694824219,0.334445
+175,Binary classification,ALMA,Phishing,0.7314285714285714,0.718562874251497,0.004366874694824219,0.511774
+200,Binary classification,ALMA,Phishing,0.735,0.7225130890052356,0.004366874694824219,0.692607
+225,Binary classification,ALMA,Phishing,0.7244444444444444,0.701923076923077,0.004366874694824219,0.876779
+250,Binary classification,ALMA,Phishing,0.724,0.7038626609442059,0.004366874694824219,1.156005
+275,Binary classification,ALMA,Phishing,0.7345454545454545,0.7137254901960783,0.004580497741699219,1.438242
+300,Binary classification,ALMA,Phishing,0.7366666666666667,0.7127272727272725,0.004580497741699219,1.723391
+325,Binary classification,ALMA,Phishing,0.7476923076923077,0.7172413793103447,0.004580497741699219,2.078902
+350,Binary classification,ALMA,Phishing,0.7542857142857143,0.7225806451612904,0.004580497741699219,2.4379969999999997
+375,Binary classification,ALMA,Phishing,0.7573333333333333,0.723404255319149,0.004580497741699219,2.8003189999999996
+400,Binary classification,ALMA,Phishing,0.76,0.7257142857142856,0.004580497741699219,3.1655669999999994
+425,Binary classification,ALMA,Phishing,0.76,0.7197802197802199,0.004580497741699219,3.585508999999999
+450,Binary classification,ALMA,Phishing,0.7622222222222222,0.7206266318537858,0.004580497741699219,4.009149999999999
+475,Binary classification,ALMA,Phishing,0.7663157894736842,0.7272727272727272,0.004580497741699219,4.435539999999999
+500,Binary classification,ALMA,Phishing,0.768,0.7327188940092165,0.004580497741699219,4.959426999999999
+525,Binary classification,ALMA,Phishing,0.7714285714285715,0.7321428571428573,0.004580497741699219,5.485955999999999
+550,Binary classification,ALMA,Phishing,0.7709090909090909,0.7341772151898734,0.004580497741699219,6.028689999999999
+575,Binary classification,ALMA,Phishing,0.7739130434782608,0.7379032258064516,0.004580497741699219,6.595545999999999
+600,Binary classification,ALMA,Phishing,0.78,0.7401574803149605,0.004580497741699219,7.165257999999999
+625,Binary classification,ALMA,Phishing,0.7744,0.7314285714285715,0.004580497741699219,7.741693999999999
+650,Binary classification,ALMA,Phishing,0.7815384615384615,0.7427536231884059,0.004580497741699219,8.363988999999998
+675,Binary classification,ALMA,Phishing,0.7837037037037037,0.75,0.004580497741699219,9.010548999999997
+700,Binary classification,ALMA,Phishing,0.79,0.7545909849749582,0.004580497741699219,9.660288999999997
+725,Binary classification,ALMA,Phishing,0.7917241379310345,0.7606973058637084,0.004580497741699219,10.349524999999996
+750,Binary classification,ALMA,Phishing,0.792,0.7621951219512195,0.004580497741699219,11.041959999999996
+775,Binary classification,ALMA,Phishing,0.792258064516129,0.7614814814814814,0.004580497741699219,11.737615999999996
+800,Binary classification,ALMA,Phishing,0.795,0.7670454545454546,0.004580497741699219,12.526707999999996
+825,Binary classification,ALMA,Phishing,0.793939393939394,0.7671232876712327,0.004580497741699219,13.319008999999996
+850,Binary classification,ALMA,Phishing,0.7976470588235294,0.7706666666666667,0.004580497741699219,14.117527999999997
+875,Binary classification,ALMA,Phishing,0.8022857142857143,0.7744458930899608,0.004580497741699219,14.959668999999996
+900,Binary classification,ALMA,Phishing,0.8011111111111111,0.7737041719342603,0.004580497741699219,15.804425999999996
+925,Binary classification,ALMA,Phishing,0.8054054054054054,0.7804878048780488,0.004580497741699219,16.651646999999997
+950,Binary classification,ALMA,Phishing,0.8073684210526316,0.7849588719153936,0.004580497741699219,17.502014999999997
+975,Binary classification,ALMA,Phishing,0.8102564102564103,0.7880870561282932,0.004580497741699219,18.418237999999995
+1000,Binary classification,ALMA,Phishing,0.811,0.7892976588628764,0.004580497741699219,19.337672999999995
+1025,Binary classification,ALMA,Phishing,0.8146341463414634,0.7943722943722944,0.004580497741699219,20.260238999999995
+1050,Binary classification,ALMA,Phishing,0.8161904761904762,0.7970557308096741,0.004580497741699219,21.242111999999995
+1075,Binary classification,ALMA,Phishing,0.815813953488372,0.7983706720977597,0.004580497741699219,22.243638999999995
+1100,Binary classification,ALMA,Phishing,0.8190909090909091,0.8023833167825224,0.004580497741699219,23.247954999999994
+1125,Binary classification,ALMA,Phishing,0.8213333333333334,0.8061716489874637,0.004580497741699219,24.273946999999993
+1150,Binary classification,ALMA,Phishing,0.8226086956521739,0.8071833648393195,0.004580497741699219,25.351544999999994
+1175,Binary classification,ALMA,Phishing,0.8212765957446808,0.8059149722735675,0.004580497741699219,26.431981999999994
+1200,Binary classification,ALMA,Phishing,0.8233333333333334,0.8076225045372051,0.004580497741699219,27.515220999999993
+1225,Binary classification,ALMA,Phishing,0.8244897959183674,0.8088888888888888,0.004580497741699219,28.636604999999992
+1250,Binary classification,ALMA,Phishing,0.8256,0.810763888888889,0.004580497741699219,29.761263999999994
+1903,Binary classification,ALMA,SMTP,0.720966894377299,0.0,0.003093719482421875,1.027868
+3806,Binary classification,ALMA,SMTP,0.7769311613242249,0.0,0.003093719482421875,3.106358
+5709,Binary classification,ALMA,SMTP,0.7509196006305833,0.0,0.003093719482421875,6.233245
+7612,Binary classification,ALMA,SMTP,0.7900683131897005,0.0,0.003093719482421875,10.302873
+9515,Binary classification,ALMA,SMTP,0.7826589595375723,0.0,0.003093719482421875,15.393504
+11418,Binary classification,ALMA,SMTP,0.7699246803293046,0.0,0.003093719482421875,21.578682
+13321,Binary classification,ALMA,SMTP,0.7722393213722694,0.0,0.003093719482421875,28.779608
+15224,Binary classification,ALMA,SMTP,0.7791644771413557,0.004146919431279621,0.003093719482421875,37.113003
+17127,Binary classification,ALMA,SMTP,0.783207800548841,0.004824443848834093,0.003093719482421875,46.3898
+19030,Binary classification,ALMA,SMTP,0.7891224382553862,0.004465393202679235,0.003093719482421875,56.715322
+20933,Binary classification,ALMA,SMTP,0.7832131084889887,0.003950834064969272,0.003093719482421875,68.217717
+22836,Binary classification,ALMA,SMTP,0.7821422315641969,0.0036050470658922497,0.003093719482421875,80.77427399999999
+24739,Binary classification,ALMA,SMTP,0.7877440478596548,0.0034162080091098878,0.003093719482421875,94.43257899999999
+26642,Binary classification,ALMA,SMTP,0.78188574431349,0.003429943405933802,0.003093719482421875,109.06303
+28545,Binary classification,ALMA,SMTP,0.7857418111753371,0.003259452411994785,0.003093719482421875,124.719605
+30448,Binary classification,ALMA,SMTP,0.7871452968996322,0.0030764497769573914,0.003093719482421875,141.369597
+32351,Binary classification,ALMA,SMTP,0.7866835646502427,0.0028897558156335793,0.003093719482421875,159.093537
+34254,Binary classification,ALMA,SMTP,0.7860979739592456,0.0027221995372260785,0.003093719482421875,177.829964
+36157,Binary classification,ALMA,SMTP,0.7771939043615345,0.0024764735017335313,0.003093719482421875,197.576045
+38060,Binary classification,ALMA,SMTP,0.7831581713084603,0.00241750271969056,0.003093719482421875,218.31617
+39963,Binary classification,ALMA,SMTP,0.779496033831294,0.002264492753623189,0.003093719482421875,240.067789
+41866,Binary classification,ALMA,SMTP,0.7831175655663307,0.0021978021978021974,0.003093719482421875,262.83473100000003
+43769,Binary classification,ALMA,SMTP,0.7791130708949257,0.002064409578860446,0.003093719482421875,286.65613700000006
+45672,Binary classification,ALMA,SMTP,0.7808066211245402,0.001993819160602133,0.003093719482421875,311.45044200000007
+47575,Binary classification,ALMA,SMTP,0.7799684708355229,0.001906941266209001,0.003093719482421875,337.28748800000005
+49478,Binary classification,ALMA,SMTP,0.7778810784591131,0.00181653042688465,0.003093719482421875,364.14950600000003
+51381,Binary classification,ALMA,SMTP,0.7807944570950351,0.0021263400372109505,0.003093719482421875,392.065506
+53284,Binary classification,ALMA,SMTP,0.7777193904361535,0.0020222446916076846,0.003093719482421875,421.04388200000005
+55187,Binary classification,ALMA,SMTP,0.7785891604906953,0.0019603038470963,0.003093719482421875,451.02283200000005
+57090,Binary classification,ALMA,SMTP,0.7758801891749869,0.002650245537454205,0.003093719482421875,482.06238400000007
+58993,Binary classification,ALMA,SMTP,0.774159646059702,0.002545481769858501,0.003093719482421875,514.138052
+60896,Binary classification,ALMA,SMTP,0.7746157383079348,0.002471109819027546,0.003093719482421875,547.227498
+62799,Binary classification,ALMA,SMTP,0.7704899759550311,0.0023534297778085413,0.003093719482421875,581.3499069999999
+64702,Binary classification,ALMA,SMTP,0.771274458285679,0.0022921863412660956,0.003093719482421875,616.580127
+66605,Binary classification,ALMA,SMTP,0.7721942797087306,0.002235812454790557,0.003093719482421875,652.800029
+68508,Binary classification,ALMA,SMTP,0.7705085537455479,0.0024111675126903555,0.003093719482421875,690.043858
+70411,Binary classification,ALMA,SMTP,0.7685872945988553,0.0023267205486162137,0.003093719482421875,728.276014
+72314,Binary classification,ALMA,SMTP,0.7687999557485411,0.002267709017127171,0.003093719482421875,767.526171
+74217,Binary classification,ALMA,SMTP,0.7657140547313958,0.0021806496040399402,0.003093719482421875,807.759105
+76120,Binary classification,ALMA,SMTP,0.7665002627430373,0.0021333932180552435,0.003093719482421875,848.897716
+78023,Binary classification,ALMA,SMTP,0.7657101111210797,0.002074462277541216,0.003093719482421875,890.953712
+79926,Binary classification,ALMA,SMTP,0.7636313590070816,0.002007395668251453,0.003093719482421875,933.942273
+81829,Binary classification,ALMA,SMTP,0.7647777682728617,0.001970341180130665,0.003093719482421875,977.888636
+83732,Binary classification,ALMA,SMTP,0.7652868676252806,0.0019298156518206286,0.003093719482421875,1022.739679
+85635,Binary classification,ALMA,SMTP,0.7642552694575816,0.0018787699001285476,0.003093719482421875,1068.5586680000001
+87538,Binary classification,ALMA,SMTP,0.7644680024674998,0.0018396591789310612,0.003093719482421875,1115.337297
+89441,Binary classification,ALMA,SMTP,0.7635312664214399,0.0018876828692779614,0.003093719482421875,1162.988807
+91344,Binary classification,ALMA,SMTP,0.7650091960063058,0.0018600325505696352,0.003093719482421875,1211.563326
+93247,Binary classification,ALMA,SMTP,0.7647859984771628,0.0018204159650480134,0.003093719482421875,1260.984755
+95150,Binary classification,ALMA,SMTP,0.7649710982658959,0.0017854751595768425,0.003093719482421875,1311.295723
+95156,Binary classification,ALMA,SMTP,0.7649859178611963,0.0017854751595768425,0.003093719482421875,1361.607838
+106,Binary classification,sklearn SGDClassifier,Bananas,0.5283018867924528,0.4680851063829788,0.005551338195800781,0.50714
+212,Binary classification,sklearn SGDClassifier,Bananas,0.5377358490566038,0.4673913043478261,0.005551338195800781,1.5449950000000001
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+636,Binary classification,sklearn SGDClassifier,Bananas,0.5235849056603774,0.3878787878787879,0.005578041076660156,10.329429000000001
+742,Binary classification,sklearn SGDClassifier,Bananas,0.5363881401617251,0.36296296296296293,0.005578041076660156,13.751562000000002
+848,Binary classification,sklearn SGDClassifier,Bananas,0.5400943396226415,0.33898305084745767,0.005578041076660156,17.710995
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+1060,Binary classification,sklearn SGDClassifier,Bananas,0.5518867924528302,0.2962962962962963,0.005578041076660156,27.154881999999997
+1166,Binary classification,sklearn SGDClassifier,Bananas,0.5523156089193825,0.27900552486187846,0.005578041076660156,32.629664
+1272,Binary classification,sklearn SGDClassifier,Bananas,0.5542452830188679,0.27586206896551724,0.005578041076660156,38.64774
+1378,Binary classification,sklearn SGDClassifier,Bananas,0.5566037735849056,0.2611850060459492,0.005578041076660156,45.182197
+1484,Binary classification,sklearn SGDClassifier,Bananas,0.557277628032345,0.24742268041237112,0.005578041076660156,52.237503000000004
+1590,Binary classification,sklearn SGDClassifier,Bananas,0.5578616352201258,0.23503808487486397,0.005578041076660156,59.74126700000001
+1696,Binary classification,sklearn SGDClassifier,Bananas,0.5595518867924528,0.22590673575129533,0.005578041076660156,67.72058500000001
+1802,Binary classification,sklearn SGDClassifier,Bananas,0.5566037735849056,0.21589793915603536,0.005578041076660156,76.17010700000002
+1908,Binary classification,sklearn SGDClassifier,Bananas,0.5545073375262054,0.21150278293135436,0.005578041076660156,85.08376800000002
+2014,Binary classification,sklearn SGDClassifier,Bananas,0.5496524329692155,0.20088105726872246,0.005578041076660156,94.42289500000003
+2120,Binary classification,sklearn SGDClassifier,Bananas,0.5466981132075471,0.19446772841575857,0.005578041076660156,104.22299500000003
+2226,Binary classification,sklearn SGDClassifier,Bananas,0.550314465408805,0.2036595067621321,0.005578041076660156,114.52672400000003
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+36157,Binary classification,sklearn SGDClassifier,SMTP,0.9996681140581354,0.5714285714285714,0.0057430267333984375,1363.9176400000001
+38060,Binary classification,sklearn SGDClassifier,SMTP,0.9996847083552286,0.5714285714285714,0.0057430267333984375,1487.072194
+39963,Binary classification,sklearn SGDClassifier,SMTP,0.9996997222430748,0.5714285714285714,0.0057430267333984375,1614.171257
+41866,Binary classification,sklearn SGDClassifier,SMTP,0.999713371232026,0.5714285714285714,0.0057430267333984375,1745.093316
+43769,Binary classification,sklearn SGDClassifier,SMTP,0.9997258333523726,0.5714285714285714,0.0057430267333984375,1880.714485
+45672,Binary classification,sklearn SGDClassifier,SMTP,0.9997372569626904,0.5714285714285714,0.0057430267333984375,2020.289668
+47575,Binary classification,sklearn SGDClassifier,SMTP,0.9997477666841829,0.5714285714285714,0.0057430267333984375,2163.67936
+49478,Binary classification,sklearn SGDClassifier,SMTP,0.9997574679655604,0.5714285714285714,0.0057430267333984375,2310.817497
+51381,Binary classification,sklearn SGDClassifier,SMTP,0.9997275257390864,0.5333333333333333,0.0057430267333984375,2461.472155
+53284,Binary classification,sklearn SGDClassifier,SMTP,0.9997372569626904,0.5333333333333333,0.0057430267333984375,2615.677493
+55187,Binary classification,sklearn SGDClassifier,SMTP,0.9997463170674253,0.5333333333333333,0.0057430267333984375,2773.449537
+57090,Binary classification,sklearn SGDClassifier,SMTP,0.999597127342792,0.41025641025641024,0.0057430267333984375,2934.793173
+58993,Binary classification,sklearn SGDClassifier,SMTP,0.9996101232349601,0.41025641025641024,0.0057430267333984375,3099.6490870000002
+60896,Binary classification,sklearn SGDClassifier,SMTP,0.9996223068838676,0.41025641025641024,0.0057430267333984375,3268.0999800000004
+62799,Binary classification,sklearn SGDClassifier,SMTP,0.9996019044889249,0.3902439024390244,0.0057430267333984375,3440.0722140000003
+64702,Binary classification,sklearn SGDClassifier,SMTP,0.9996136131804272,0.3902439024390244,0.0057430267333984375,3615.5032180000003
+66605,Binary classification,sklearn SGDClassifier,SMTP,0.9996246528038436,0.3902439024390244,0.0057430267333984375,3794.4378890000003
+68508,Binary classification,sklearn SGDClassifier,SMTP,0.9996058854440357,0.37209302325581395,0.0057430267333984375,3977.0945010000005
+70411,Binary classification,sklearn SGDClassifier,SMTP,0.9996165371887915,0.37209302325581395,0.0057430267333984375,4163.174128000001
+72314,Binary classification,sklearn SGDClassifier,SMTP,0.9996266283154023,0.37209302325581395,0.0057430267333984375,4352.606393000001
+74217,Binary classification,sklearn SGDClassifier,SMTP,0.9996362019483407,0.37209302325581395,0.0057430267333984375,4545.416162000001
+76120,Binary classification,sklearn SGDClassifier,SMTP,0.9996452968996321,0.37209302325581395,0.0057430267333984375,4741.562007000001
+78023,Binary classification,sklearn SGDClassifier,SMTP,0.999653948194763,0.37209302325581395,0.0057430267333984375,4941.079189000001
+79926,Binary classification,sklearn SGDClassifier,SMTP,0.9996621875234591,0.37209302325581395,0.0057430267333984375,5143.951781000001
+81829,Binary classification,sklearn SGDClassifier,SMTP,0.9996700436275648,0.37209302325581395,0.0057430267333984375,5350.231536
+83732,Binary classification,sklearn SGDClassifier,SMTP,0.9996775426360293,0.37209302325581395,0.0057430267333984375,5559.929647
+85635,Binary classification,sklearn SGDClassifier,SMTP,0.9996847083552286,0.37209302325581395,0.0057430267333984375,5773.003953
+87538,Binary classification,sklearn SGDClassifier,SMTP,0.9996915625214192,0.37209302325581395,0.0057430267333984375,5989.467769000001
+89441,Binary classification,sklearn SGDClassifier,SMTP,0.9996869444661844,0.36363636363636365,0.0057430267333984375,6209.264779000001
+91344,Binary classification,sklearn SGDClassifier,SMTP,0.9996934664564723,0.36363636363636365,0.0057430267333984375,6432.452666000001
+93247,Binary classification,sklearn SGDClassifier,SMTP,0.9996997222430748,0.36363636363636365,0.0057430267333984375,6658.918178000001
+95150,Binary classification,sklearn SGDClassifier,SMTP,0.9997057277982133,0.36363636363636365,0.0057430267333984375,6888.546542000001
+95156,Binary classification,sklearn SGDClassifier,SMTP,0.9997057463533566,0.36363636363636365,0.0057430267333984375,7118.179378000001
+106,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5,0.0,0.0006465911865234375,0.16057
+212,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5283018867924528,0.0,0.0006465911865234375,0.37729
+318,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5314465408805031,0.0,0.0006465911865234375,0.7064710000000001
+424,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5400943396226415,0.0,0.0006465911865234375,1.0774430000000002
+530,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5547169811320755,0.0,0.0006465911865234375,1.4923790000000001
+636,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5550314465408805,0.0,0.0006465911865234375,1.9966470000000003
+742,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5660377358490566,0.0,0.0006465911865234375,2.539797
+848,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5636792452830188,0.0,0.0006465911865234375,3.1757850000000003
+954,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5649895178197065,0.0,0.0006465911865234375,3.8551140000000004
+1060,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5707547169811321,0.0,0.0006465911865234375,4.635951
+1166,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5686106346483705,0.0,0.0006465911865234375,5.458947
+1272,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5644654088050315,0.0,0.0006465911865234375,6.34328
+1378,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5682148040638607,0.0,0.0006465911865234375,7.308669
+1484,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5680592991913747,0.0,0.0006465911865234375,8.359952
+1590,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5679245283018868,0.0,0.0006465911865234375,9.451883
+1696,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5683962264150944,0.0,0.0006465911865234375,10.590847
+1802,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5643729189789123,0.0,0.0006465911865234375,11.83715
+1908,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.560272536687631,0.0,0.0006465911865234375,13.126961999999999
+2014,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5551142005958292,0.0,0.0006465911865234375,14.497203999999998
+2120,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5509433962264151,0.0,0.0006465911865234375,15.938437999999998
+2226,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5512129380053908,0.0,0.0006465911865234375,17.424999
+2332,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5506003430531733,0.0,0.0006465911865234375,19.022886
+2438,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.551681706316653,0.0,0.0006465911865234375,20.666828
+2544,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5487421383647799,0.0,0.0006465911865234375,22.355415999999998
+2650,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5467924528301886,0.0,0.0006465911865234375,24.051772
+2756,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5471698113207547,0.0,0.0006465911865234375,25.858309
+2862,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5489168413696716,0.0,0.0006465911865234375,27.751458999999997
+2968,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5505390835579514,0.0,0.0006465911865234375,29.665551999999998
+3074,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5487963565387117,0.0,0.0006465911865234375,31.686176
+3180,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5509433962264151,0.0,0.0006465911865234375,33.740652
+3286,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5517346317711503,0.0,0.0006465911865234375,35.89104
+3392,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5498231132075472,0.0,0.0006465911865234375,38.079414
+3498,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5514579759862779,0.0,0.0006465911865234375,40.353903
+3604,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5535516093229744,0.0,0.0006465911865234375,42.668922
+3710,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5522911051212938,0.0,0.0006465911865234375,45.086801
+3816,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5516247379454927,0.0,0.0006465911865234375,47.540759
+3922,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5525242223355431,0.0,0.0006465911865234375,50.094246
+4028,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5528798411122146,0.0,0.0006465911865234375,52.697210999999996
+4134,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5529753265602322,0.0,0.0006465911865234375,55.369586999999996
+4240,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5523584905660377,0.0,0.0006465911865234375,58.109435999999995
+4346,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5526921306948919,0.0,0.0006465911865234375,60.894093
+4452,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5530098831985625,0.0,0.0006465911865234375,63.717346
+4558,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5508995173321632,0.0,0.0006465911865234375,66.643891
+4664,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5497427101200686,0.0,0.0006465911865234375,69.6601
+4770,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5505241090146751,0.0,0.0006465911865234375,72.725555
+4876,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5518867924528302,0.0,0.0006465911865234375,75.798736
+4982,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5509835407466881,0.0,0.0006465911865234375,78.970205
+5088,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5511006289308176,0.0,0.0006465911865234375,82.150165
+5194,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5514054678475163,0.0,0.0006465911865234375,85.416127
+5300,Binary classification,Vowpal Wabbit logistic regression,Bananas,0.5513207547169812,0.0,0.0006465911865234375,88.72481
+906,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6799116997792495,0.5482866043613708,0.0006465911865234375,0.820242
+1812,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.7190949227373068,0.4904904904904904,0.0006465911865234375,2.329863
+2718,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6986754966887417,0.43243243243243246,0.0006465911865234375,4.585071
+3624,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.7047461368653422,0.4478844169246646,0.0006465911865234375,7.424633
+4530,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.7024282560706402,0.4118673647469459,0.0006465911865234375,10.992865
+5436,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.7041942604856513,0.4165457184325108,0.0006465911865234375,15.263433
+6342,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6986754966887417,0.40485829959514175,0.0006465911865234375,20.287067999999998
+7248,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.695364238410596,0.3953997809419496,0.0006465911865234375,26.004013999999998
+8154,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6873926907039489,0.4084474355999072,0.0006465911865234375,32.433811999999996
+9060,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6864238410596026,0.42408270829110073,0.0006465911865234375,39.59982599999999
+9966,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.687537627934979,0.4433321415802646,0.0006465911865234375,47.447314999999996
+10872,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6938925680647535,0.4717460317460317,0.0006465911865234375,55.964904999999995
+11778,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6932416369502462,0.47155185022670765,0.0006465911865234375,65.217817
+12684,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6944970040996531,0.47557179591284343,0.0006465911865234375,75.258293
+13590,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6942604856512141,0.48429936701005344,0.0006465911865234375,85.993354
+14496,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6935016556291391,0.48606130711393875,0.0006465911865234375,97.389046
+15402,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6929619529931178,0.48095708484249805,0.0006465911865234375,109.49806
+16308,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6904586705911209,0.47130289065772935,0.0006465911865234375,122.273049
+17214,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6921691646334379,0.4645852278468223,0.0006465911865234375,135.723897
+18120,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.694205298013245,0.46859115757168884,0.0006465911865234375,150.008391
+19026,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6967307894460212,0.467515688445921,0.0006465911865234375,164.94785199999998
+19932,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6958157736303432,0.4737435986459509,0.0006465911865234375,180.578389
+20838,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6933966791438718,0.4696604963891426,0.0006465911865234375,196.972492
+21744,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6968359087564385,0.4670978172999191,0.0006465911865234375,214.03759399999998
+22650,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6977041942604857,0.4643667370726746,0.0006465911865234375,231.758696
+23556,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6952368823229751,0.4573285962657797,0.0006465911865234375,250.24763199999998
+24462,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6978170223203336,0.4597281099254495,0.0006465911865234375,269.425119
+25368,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6976505834121728,0.46122506322000567,0.0006465911865234375,289.286378
+26274,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6983329527289336,0.4614757439869547,0.0006465911865234375,309.833587
+27180,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6959896983075791,0.4576304561864129,0.0006465911865234375,331.075152
+28086,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.695649077832372,0.4559572301425662,0.0006465911865234375,353.085242
+28992,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6952262693156733,0.4515207945375543,0.0006465911865234375,375.713328
+29898,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6939260151180681,0.4465678863017841,0.0006465911865234375,399.011341
+30804,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6941630957018569,0.44330201500915917,0.0006465911865234375,423.007885
+31710,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6917376222011984,0.4368266405484819,0.0006465911865234375,447.82068599999997
+32616,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6893549178317391,0.4316805025802109,0.0006465911865234375,473.25918699999994
+33522,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.688353916830738,0.42909448603748845,0.0006465911865234375,499.4094079999999
+34428,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6863599395840595,0.4245363461948412,0.0006465911865234375,526.1781749999999
+35334,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6869304352748061,0.4212013394725827,0.0006465911865234375,553.6489789999999
+36240,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6911147902869758,0.4267718148299877,0.0006465911865234375,581.8684239999999
+37146,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6919722177354224,0.42698317307692313,0.0006465911865234375,610.7708879999999
+38052,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6944181646168401,0.43117111828588206,0.0006465911865234375,640.2659799999999
+38958,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6937727809435803,0.43082061068702293,0.0006465911865234375,670.4759659999999
+39864,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6930814770218744,0.4344288818009522,0.0006465911865234375,701.3646249999998
+40770,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6924208977189109,0.4391771019677997,0.0006465911865234375,733.0001779999998
+41676,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6933966791438718,0.44722270288977334,0.0006465911865234375,765.3741459999998
+42582,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6956225635244939,0.45507672903090185,0.0006465911865234375,798.4329459999998
+43488,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6962150478292862,0.4576097220511558,0.0006465911865234375,832.1587539999998
+44394,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6963103122043519,0.45575649927337314,0.0006465911865234375,866.6068249999998
+45300,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.697439293598234,0.4596278189560006,0.0006465911865234375,901.8081399999999
+45312,Binary classification,Vowpal Wabbit logistic regression,Elec2,0.6974752824858758,0.45959157927935035,0.0006465911865234375,937.0113409999999
+25,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.52,0.33333333333333337,0.0006465911865234375,0.00395
+50,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.56,0.21428571428571427,0.0006465911865234375,0.07842199999999999
+75,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.5866666666666667,0.3404255319148936,0.0006465911865234375,0.15624899999999997
+100,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.6,0.375,0.0006465911865234375,0.23731799999999997
+125,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.64,0.4705882352941176,0.0006465911865234375,0.41813199999999995
+150,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.62,0.44660194174757284,0.0006465911865234375,0.6021909999999999
+175,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.6342857142857142,0.41818181818181815,0.0006465911865234375,0.7890869999999999
+200,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.63,0.4126984126984127,0.0006465911865234375,1.0120959999999999
+225,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.6488888888888888,0.4316546762589928,0.0006465911865234375,1.2378889999999998
+250,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.648,0.4358974358974359,0.0006465911865234375,1.4692909999999997
+275,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.6618181818181819,0.4561403508771929,0.0006465911865234375,1.7531039999999996
+300,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.6733333333333333,0.46153846153846156,0.0006465911865234375,2.0408739999999996
+325,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.683076923076923,0.46632124352331616,0.0006465911865234375,2.33165
+350,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.6942857142857143,0.47804878048780486,0.0006465911865234375,2.715045
+375,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7013333333333334,0.4909090909090909,0.0006465911865234375,3.1015189999999997
+400,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.705,0.4913793103448276,0.0006465911865234375,3.4910129999999997
+425,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7105882352941176,0.4896265560165975,0.0006465911865234375,3.9231499999999997
+450,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7222222222222222,0.5098039215686275,0.0006465911865234375,4.358171
+475,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7157894736842105,0.5054945054945055,0.0006465911865234375,4.7960329999999995
+500,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.718,0.5252525252525252,0.0006465911865234375,5.248043999999999
+525,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7257142857142858,0.5294117647058824,0.0006465911865234375,5.702586999999999
+550,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7218181818181818,0.5233644859813085,0.0006465911865234375,6.1599829999999995
+575,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7217391304347827,0.5209580838323353,0.0006465911865234375,6.620335
+600,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7283333333333334,0.5275362318840581,0.0006465911865234375,7.1135079999999995
+625,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7376,0.5340909090909091,0.0006465911865234375,7.613357
+650,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7369230769230769,0.5415549597855228,0.0006465911865234375,8.116107
+675,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7333333333333333,0.5477386934673367,0.0006465911865234375,8.713363
+700,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.74,0.5560975609756097,0.0006465911865234375,9.313647
+725,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.743448275862069,0.5753424657534246,0.0006465911865234375,9.917033
+750,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7453333333333333,0.5820568927789934,0.0006465911865234375,10.613639
+775,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7470967741935484,0.5847457627118644,0.0006465911865234375,11.313362999999999
+800,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.74625,0.5915492957746479,0.0006465911865234375,12.015877
+825,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7490909090909091,0.602687140115163,0.0006465911865234375,12.766805
+850,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7541176470588236,0.6122448979591837,0.0006465911865234375,13.520246
+875,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7554285714285714,0.6123188405797102,0.0006465911865234375,14.2887
+900,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7566666666666667,0.6123893805309735,0.0006465911865234375,15.059985000000001
+925,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.76,0.6237288135593221,0.0006465911865234375,15.877357000000002
+950,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7589473684210526,0.6288492706645057,0.0006465911865234375,16.697524
+975,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7610256410256411,0.631911532385466,0.0006465911865234375,17.562951
+1000,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.761,0.6328725038402457,0.0006465911865234375,18.43148
+1025,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7609756097560976,0.635958395245171,0.0006465911865234375,19.325245
+1050,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7638095238095238,0.6436781609195402,0.0006465911865234375,20.222005
+1075,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7665116279069767,0.651872399445215,0.0006465911865234375,21.121639
+1100,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.77,0.6594885598923284,0.0006465911865234375,22.071389
+1125,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.768,0.6597131681877444,0.0006465911865234375,23.024294
+1150,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7695652173913043,0.6615581098339719,0.0006465911865234375,23.980116000000002
+1175,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7702127659574468,0.6633416458852868,0.0006465911865234375,24.939110000000003
+1200,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7741666666666667,0.6691086691086692,0.0006465911865234375,25.901192
+1225,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7771428571428571,0.6746126340882003,0.0006465911865234375,26.865956
+1250,Binary classification,Vowpal Wabbit logistic regression,Phishing,0.7736,0.6697782963827306,0.0006465911865234375,27.833412
+1903,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,1.287853
+3806,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,3.7805989999999996
+5709,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,7.576109
+7612,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,12.534125
+9515,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,18.771881
+11418,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,26.322128
+13321,Binary classification,Vowpal Wabbit logistic regression,SMTP,1.0,0.0,0.0006465911865234375,35.214625
+15224,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9992774566473989,0.0,0.0006465911865234375,45.441497999999996
+17127,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999299351900508,0.14285714285714288,0.0006465911865234375,56.927386
+19030,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9993694167104572,0.14285714285714288,0.0006465911865234375,69.74153799999999
+20933,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9994267424640519,0.14285714285714288,0.0006465911865234375,83.765543
+22836,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999474513925381,0.14285714285714288,0.0006465911865234375,99.06549199999999
+24739,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999514935931121,0.14285714285714288,0.0006465911865234375,115.581943
+26642,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995120486449967,0.13333333333333333,0.0006465911865234375,133.361343
+28545,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995445787353302,0.13333333333333333,0.0006465911865234375,152.36548100000002
+30448,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995730425643721,0.13333333333333333,0.0006465911865234375,172.57866
+32351,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995981577076443,0.13333333333333333,0.0006465911865234375,193.96982500000001
+34254,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996204822794418,0.13333333333333333,0.0006465911865234375,216.600052
+36157,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996404568963133,0.13333333333333333,0.0006465911865234375,240.511883
+38060,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996584340514977,0.13333333333333333,0.0006465911865234375,265.709607
+39963,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996746990966644,0.13333333333333333,0.0006465911865234375,292.142637
+41866,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996894855013615,0.13333333333333333,0.0006465911865234375,319.87834699999996
+43769,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999702986131737,0.13333333333333333,0.0006465911865234375,348.79444399999994
+45672,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9997153617095814,0.13333333333333333,0.0006465911865234375,378.9697039999999
+47575,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9997267472411981,0.13333333333333333,0.0006465911865234375,410.4053809999999
+49478,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9997372569626904,0.13333333333333333,0.0006465911865234375,443.05761399999994
+51381,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9997080632918783,0.11764705882352941,0.0006465911865234375,477.02532299999996
+53284,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9997184896028827,0.11764705882352941,0.0006465911865234375,512.247669
+55187,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9997281968579557,0.11764705882352941,0.0006465911865234375,548.612896
+57090,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995796111403048,0.14285714285714285,0.0006465911865234375,586.233337
+58993,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995931720712626,0.14285714285714285,0.0006465911865234375,625.057298
+60896,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996058854440357,0.14285714285714285,0.0006465911865234375,665.0820319999999
+62799,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999585980668482,0.13333333333333333,0.0006465911865234375,706.1803269999999
+64702,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995981577076443,0.13333333333333333,0.0006465911865234375,748.3509649999999
+66605,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996096389159973,0.13333333333333333,0.0006465911865234375,791.6670189999999
+68508,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9995912886086297,0.125,0.0006465911865234375,836.0877649999999
+70411,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996023348624504,0.125,0.0006465911865234375,881.7116259999999
+72314,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996127997344912,0.125,0.0006465911865234375,928.538605
+74217,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996227279464274,0.125,0.0006465911865234375,976.4092069999999
+76120,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996321597477666,0.125,0.0006465911865234375,1025.3623619999998
+78023,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996411314612358,0.125,0.0006465911865234375,1075.4142359999998
+79926,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999649675950254,0.125,0.0006465911865234375,1126.58116
+81829,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996578230211783,0.125,0.0006465911865234375,1178.778759
+83732,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999665599770697,0.125,0.0006465911865234375,1231.992839
+85635,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996730308869037,0.125,0.0006465911865234375,1286.303482
+87538,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996801389111014,0.125,0.0006465911865234375,1341.617815
+89441,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996757639114053,0.1212121212121212,0.0006465911865234375,1397.839199
+91344,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996825188299177,0.1212121212121212,0.0006465911865234375,1455.075933
+93247,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996889980374704,0.1212121212121212,0.0006465911865234375,1513.261041
+95150,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.999695218076721,0.1212121212121212,0.0006465911865234375,1572.312523
+95156,Binary classification,Vowpal Wabbit logistic regression,SMTP,0.9996952372945479,0.1212121212121212,0.0006465911865234375,1631.3703540000001
+106,Binary classification,Naive Bayes,Bananas,0.5333333333333333,0.46153846153846156,0.014024734497070312,0.089081
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+3180,Binary classification,Naive Bayes,Bananas,0.6071091538219566,0.4077761972498815,0.014024734497070312,36.007059
+3286,Binary classification,Naive Bayes,Bananas,0.6063926940639269,0.4049700874367234,0.014024734497070312,38.312687
+3392,Binary classification,Naive Bayes,Bananas,0.6048363314656443,0.40602836879432624,0.014024734497070312,40.720333999999994
+3498,Binary classification,Naive Bayes,Bananas,0.6065198741778668,0.40535868625756266,0.014024734497070312,43.213055999999995
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+3710,Binary classification,Naive Bayes,Bananas,0.6085198166621731,0.4078303425774878,0.014024734497070312,48.41046399999999
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+4452,Binary classification,Naive Bayes,Bananas,0.6137946528869916,0.413510747185261,0.014024734497070312,69.16846599999998
+4558,Binary classification,Naive Bayes,Bananas,0.6122448979591837,0.4115884115884116,0.014024734497070312,72.34300699999999
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+4982,Binary classification,Naive Bayes,Bananas,0.6163420999799237,0.41684467500762895,0.014024734497070312,86.09394899999998
+5088,Binary classification,Naive Bayes,Bananas,0.6150973068606251,0.41412327947336924,0.014024734497070312,89.70897599999998
+5194,Binary classification,Naive Bayes,Bananas,0.6146735990756788,0.4133685136323659,0.014024734497070312,93.40231399999998
+5300,Binary classification,Naive Bayes,Bananas,0.6152104170598226,0.4139120436907157,0.014024734497070312,97.15397799999998
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+1812,Binary classification,Naive Bayes,Elec2,0.8023191606847045,0.7475317348377998,0.05103778839111328,2.6687279999999998
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+3624,Binary classification,Naive Bayes,Elec2,0.8032017664918576,0.7356321839080461,0.05103778839111328,8.965856
+4530,Binary classification,Naive Bayes,Elec2,0.7979686465003312,0.7073872721458268,0.05103778839111328,13.460125000000001
+5436,Binary classification,Naive Bayes,Elec2,0.7937442502299908,0.6972724817715366,0.05103778839111328,18.947959
+6342,Binary classification,Naive Bayes,Elec2,0.7982967986122063,0.7065840789171829,0.05103778839111328,25.368016
+7248,Binary classification,Naive Bayes,Elec2,0.790396025941769,0.6875128574367414,0.05103778839111328,32.74734
+8154,Binary classification,Naive Bayes,Elec2,0.7841285416411137,0.6888260254596887,0.05103778839111328,41.092102
+9060,Binary classification,Naive Bayes,Elec2,0.7897118887294403,0.7086710506193606,0.05103778839111328,50.330248999999995
+9966,Binary classification,Naive Bayes,Elec2,0.793176116407426,0.7240594457089301,0.05103778839111328,60.487047999999994
+10872,Binary classification,Naive Bayes,Elec2,0.7960629196946003,0.7361656551231703,0.05103778839111328,71.57583
+11778,Binary classification,Naive Bayes,Elec2,0.792137216608644,0.7295027624309391,0.05103778839111328,83.57396899999999
+12684,Binary classification,Naive Bayes,Elec2,0.7820704880548766,0.7260111022997621,0.05103778839111328,96.50585899999999
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+14496,Binary classification,Naive Bayes,Elec2,0.7866850638151086,0.7435727317963178,0.05103778839111328,125.16282799999999
+15402,Binary classification,Naive Bayes,Elec2,0.785728199467567,0.738593155893536,0.05103778839111328,140.864825
+16308,Binary classification,Naive Bayes,Elec2,0.7806463481940271,0.7274666666666666,0.05103778839111328,157.49451299999998
+17214,Binary classification,Naive Bayes,Elec2,0.7788880497298554,0.7181158346911569,0.05103778839111328,175.04662
+18120,Binary classification,Naive Bayes,Elec2,0.7728903361112645,0.7138983522213725,0.05103778839111328,193.53438899999998
+19026,Binary classification,Naive Bayes,Elec2,0.7701445466491459,0.7094931242941608,0.05103778839111328,212.92156899999998
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+2438,Binary classification,Hoeffding Tree,Bananas,0.606893721789085,0.388250319284802,0.019248008728027344,21.528239
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+2650,Binary classification,Hoeffding Tree,Bananas,0.6070215175537939,0.3944153577661431,0.019248008728027344,25.108421
+2756,Binary classification,Hoeffding Tree,Bananas,0.6047186932849364,0.3892316320807628,0.019248008728027344,26.99552
+2862,Binary classification,Hoeffding Tree,Bananas,0.6057322614470465,0.3922413793103448,0.019248008728027344,28.904989
+2968,Binary classification,Hoeffding Tree,Bananas,0.6056622851365016,0.3899895724713243,0.019248008728027344,30.87684
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+3180,Binary classification,Hoeffding Tree,Bananas,0.6045926391947153,0.3924601256645723,0.019248008728027344,35.112766
+3286,Binary classification,Hoeffding Tree,Bananas,0.6039573820395738,0.39006094702297234,0.019248008728027344,37.308874
+3392,Binary classification,Hoeffding Tree,Bananas,0.6024771453848422,0.39169675090252704,0.019248008728027344,39.588614
+3498,Binary classification,Hoeffding Tree,Bananas,0.6030883614526737,0.39335664335664333,0.03483390808105469,41.900558
+3604,Binary classification,Hoeffding Tree,Bananas,0.6069941715237303,0.40353833192923344,0.03483390808105469,44.304379999999995
+3710,Binary classification,Hoeffding Tree,Bananas,0.6079805877595039,0.40798045602605865,0.03483390808105469,46.776579
+3816,Binary classification,Hoeffding Tree,Bananas,0.6107470511140236,0.4146629877808436,0.03483390808105469,49.299973
+3922,Binary classification,Hoeffding Tree,Bananas,0.6123437898495282,0.4180704441041348,0.04409217834472656,51.9923
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+4134,Binary classification,Hoeffding Tree,Bananas,0.617227195741592,0.43216080402010054,0.05025672912597656,57.554127
+4240,Binary classification,Hoeffding Tree,Bananas,0.6218447747110167,0.4439819632327437,0.05025672912597656,60.441345
+4346,Binary classification,Hoeffding Tree,Bananas,0.6239355581127733,0.45130960376091334,0.05025672912597656,63.387968
+4452,Binary classification,Hoeffding Tree,Bananas,0.6259267580319029,0.45676998368678623,0.05025672912597656,66.368103
+4558,Binary classification,Hoeffding Tree,Bananas,0.6276058810621022,0.46382306477093216,0.05025672912597656,69.45485500000001
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+4770,Binary classification,Hoeffding Tree,Bananas,0.6288530090165653,0.47164179104477605,0.05941963195800781,75.94439200000001
+4876,Binary classification,Hoeffding Tree,Bananas,0.6311794871794871,0.47580174927113705,0.05946540832519531,79.31100500000001
+4982,Binary classification,Hoeffding Tree,Bananas,0.6336077092953222,0.484026010743568,0.05946540832519531,82.69585900000001
+5088,Binary classification,Hoeffding Tree,Bananas,0.6361313151169649,0.49050371593724196,0.05946540832519531,86.19871000000002
+5194,Binary classification,Hoeffding Tree,Bananas,0.6383593298671288,0.495703544575725,0.05946540832519531,89.82165300000003
+5300,Binary classification,Hoeffding Tree,Bananas,0.6421966408756369,0.5034049240440022,0.05946540832519531,93.53024900000003
+906,Binary classification,Hoeffding Tree,Elec2,0.8530386740331491,0.8513966480446927,0.1757516860961914,1.081486
+1812,Binary classification,Hoeffding Tree,Elec2,0.8663721700717836,0.8393094289508632,0.2084512710571289,3.2087309999999998
+2718,Binary classification,Hoeffding Tree,Elec2,0.8365844681634156,0.809278350515464,0.23302173614501953,6.394793
+3624,Binary classification,Hoeffding Tree,Elec2,0.8459839911675407,0.8210391276459269,0.23302173614501953,10.694791
+4530,Binary classification,Hoeffding Tree,Elec2,0.8511812762199161,0.8157463094587206,0.23296833038330078,16.02834
+5436,Binary classification,Hoeffding Tree,Elec2,0.8404783808647655,0.8020095912308747,0.23296833038330078,22.571918
+6342,Binary classification,Hoeffding Tree,Elec2,0.8334647531935025,0.7966884867154409,0.23296833038330078,30.238204
+7248,Binary classification,Hoeffding Tree,Elec2,0.8330343590451221,0.7912353347135956,0.23296833038330078,38.961308
+8154,Binary classification,Hoeffding Tree,Elec2,0.8344167790997179,0.8013537374926426,0.23296833038330078,48.732242
+9060,Binary classification,Hoeffding Tree,Elec2,0.8403797328623468,0.8129849974133472,0.2980508804321289,59.636444
+9966,Binary classification,Hoeffding Tree,Elec2,0.8398394380331159,0.8171402383134739,0.29816532135009766,71.55266999999999
+10872,Binary classification,Hoeffding Tree,Elec2,0.840493054916751,0.8200124558854057,0.29816532135009766,84.613385
+11778,Binary classification,Hoeffding Tree,Elec2,0.8404517279442982,0.8184014690248381,0.3811311721801758,98.771271
+12684,Binary classification,Hoeffding Tree,Elec2,0.8397066939998423,0.8184983483617534,0.3811311721801758,114.088656
+13590,Binary classification,Hoeffding Tree,Elec2,0.8422253293104717,0.8228684732319893,0.3811311721801758,130.484857
+14496,Binary classification,Hoeffding Tree,Elec2,0.8440841669541221,0.8259128023417038,0.38237476348876953,148.034702
+15402,Binary classification,Hoeffding Tree,Elec2,0.8445555483410169,0.8246153846153847,0.3824014663696289,166.630313
+16308,Binary classification,Hoeffding Tree,Elec2,0.8382903047770895,0.8146221441124781,0.40816211700439453,186.33286
+17214,Binary classification,Hoeffding Tree,Elec2,0.8345436588624876,0.8052516411378555,0.40816211700439453,207.14980100000002
+18120,Binary classification,Hoeffding Tree,Elec2,0.8332689442022186,0.8030253635000325,0.40884876251220703,229.10312700000003
+19026,Binary classification,Hoeffding Tree,Elec2,0.8340604467805519,0.8008327550312283,0.4101419448852539,252.19556200000002
+19932,Binary classification,Hoeffding Tree,Elec2,0.8288595655009784,0.7951228302000121,0.4740419387817383,276.349221
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+22650,Binary classification,Hoeffding Tree,Elec2,0.8245838668373879,0.7828843106180666,0.4754457473754883,356.18046400000003
+23556,Binary classification,Hoeffding Tree,Elec2,0.81761834005519,0.7712703652433182,0.5000581741333008,385.033694
+24462,Binary classification,Hoeffding Tree,Elec2,0.8151342954090184,0.7656509121061359,0.5002222061157227,415.059878
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+26274,Binary classification,Hoeffding Tree,Elec2,0.8142199215925094,0.7659329592864336,0.5574884414672852,478.875266
+27180,Binary classification,Hoeffding Tree,Elec2,0.8130909893667906,0.7650758416574177,0.5574884414672852,512.642228
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+36240,Binary classification,Hoeffding Tree,Elec2,0.798283617097602,0.7418420680887131,0.8215837478637695,916.0524170000001
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+1903,Binary classification,Hoeffding Tree,SMTP,1.0,0.0,0.01702117919921875,1.086226
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+9515,Binary classification,Hoeffding Tree,SMTP,1.0,0.0,0.01702117919921875,15.968691
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+45672,Binary classification,Hoeffding Tree,SMTP,0.9996934597446958,0.0,0.0170440673828125,346.89099000000004
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+49478,Binary classification,Hoeffding Tree,SMTP,0.99971704024092,0.0,0.0170440673828125,407.49804200000005
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+53284,Binary classification,Hoeffding Tree,SMTP,0.9996997166075484,0.0,0.0170440673828125,472.95335100000005
+55187,Binary classification,Hoeffding Tree,SMTP,0.999710071394919,0.0,0.0170440673828125,507.47402400000004
+57090,Binary classification,Hoeffding Tree,SMTP,0.9995620872672494,0.0,0.0170440673828125,543.2100710000001
+58993,Binary classification,Hoeffding Tree,SMTP,0.9995762137238947,0.0,0.0170440673828125,580.098547
+60896,Binary classification,Hoeffding Tree,SMTP,0.999589457262501,0.0,0.0170440673828125,618.1800870000001
+62799,Binary classification,Hoeffding Tree,SMTP,0.9995700500015924,0.0,0.0170440673828125,657.2504170000001
+64702,Binary classification,Hoeffding Tree,SMTP,0.9995826957852274,0.0,0.0170440673828125,697.447209
+66605,Binary classification,Hoeffding Tree,SMTP,0.9995946189418053,0.0,0.0170440673828125,738.7766780000001
+68508,Binary classification,Hoeffding Tree,SMTP,0.9995766855941729,0.0,0.0170440673828125,781.207926
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+72314,Binary classification,Hoeffding Tree,SMTP,0.9995989656078437,0.0,0.0170440673828125,869.3947840000001
+74217,Binary classification,Hoeffding Tree,SMTP,0.99960924867953,0.0,0.0170440673828125,915.176721
+76120,Binary classification,Hoeffding Tree,SMTP,0.9996190175908775,0.0,0.0170440673828125,961.985028
+78023,Binary classification,Hoeffding Tree,SMTP,0.9996283099638563,0.0,0.0170440673828125,1009.890756
+79926,Binary classification,Hoeffding Tree,SMTP,0.9996371598373475,0.0,0.0170440673828125,1058.848202
+81829,Binary classification,Hoeffding Tree,SMTP,0.9996455980837855,0.0,0.0170440673828125,1108.7919539999998
+83732,Binary classification,Hoeffding Tree,SMTP,0.9996536527689864,0.0,0.0170440673828125,1159.7893379999998
+85635,Binary classification,Hoeffding Tree,SMTP,0.999661349463998,0.0,0.0170440673828125,1211.840415
+87538,Binary classification,Hoeffding Tree,SMTP,0.9996687115162731,0.0,0.0170440673828125,1264.8087919999998
+89441,Binary classification,Hoeffding Tree,SMTP,0.9996645796064401,0.0,0.0170440673828125,1318.8158339999998
+91344,Binary classification,Hoeffding Tree,SMTP,0.999671567607808,0.0,0.0170440673828125,1373.8298589999997
+93247,Binary classification,Hoeffding Tree,SMTP,0.9996782703815713,0.0,0.0170440673828125,1429.7685149999998
+95150,Binary classification,Hoeffding Tree,SMTP,0.9996847050415664,0.0,0.0170440673828125,1486.6476859999998
+95156,Binary classification,Hoeffding Tree,SMTP,0.9996847249224948,0.0,0.0170440673828125,1543.5553739999998
+106,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5714285714285714,0.628099173553719,0.025684356689453125,0.216494
+212,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5592417061611374,0.5903083700440529,0.025768280029296875,0.463954
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+636,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5543307086614173,0.5291181364392679,0.025890350341796875,2.6939569999999997
+742,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5708502024291497,0.5167173252279634,0.025890350341796875,3.4801279999999997
+848,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5761511216056671,0.510231923601637,0.025890350341796875,4.453125999999999
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+1166,Binary classification,Hoeffding Adaptive Tree,Bananas,0.590557939914163,0.478688524590164,0.025890350341796875,8.08575
+1272,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5971675845790716,0.48073022312373226,0.025890350341796875,9.558451000000002
+1378,Binary classification,Hoeffding Adaptive Tree,Bananas,0.599128540305011,0.4661508704061895,0.025951385498046875,11.087295000000001
+1484,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5994605529332434,0.458029197080292,0.025951385498046875,12.740385000000002
+1590,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5997482693517936,0.4517241379310345,0.025951385498046875,14.490633000000003
+1696,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6011799410029498,0.4459016393442623,0.025951385498046875,16.383274000000004
+1802,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6018878400888396,0.44547563805104406,0.025951385498046875,18.381747000000004
+1908,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6030414263240692,0.44704163623082543,0.025951385498046875,20.420329000000002
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+2120,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5960358659745163,0.4427083333333333,0.025951385498046875,24.891681000000002
+2226,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5968539325842697,0.4425108763206961,0.025951385498046875,27.295309000000003
+2332,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5975975975975976,0.44233055885850175,0.025951385498046875,29.792211
+2438,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5982765695527288,0.4396107613050944,0.025951385498046875,32.414577
+2544,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5973259929217459,0.4398249452954048,0.03029155731201172,35.17394
+2650,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5956964892412231,0.44363636363636366,0.056708335876464844,38.067898
+2756,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5985480943738657,0.44975124378109455,0.056952476501464844,41.158639
+2862,Binary classification,Hoeffding Adaptive Tree,Bananas,0.600139811254806,0.4536771728748806,0.057196617126464844,44.452629
+2968,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5979103471520054,0.45250114731528224,0.057303428649902344,47.888765
+3074,Binary classification,Hoeffding Adaptive Tree,Bananas,0.5971363488447771,0.4497777777777778,0.057425498962402344,51.476908
+3180,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6008178672538534,0.44993498049414826,0.057486534118652344,55.178717
+3286,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6024353120243531,0.4470787468247248,0.057608604431152344,59.035765
+3392,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6012975523444412,0.444991789819376,0.057669639587402344,63.084021
+3498,Binary classification,Hoeffding Adaptive Tree,Bananas,0.603946239633972,0.44310414153598715,0.057730674743652344,67.283017
+3604,Binary classification,Hoeffding Adaptive Tree,Bananas,0.607826810990841,0.4452296819787986,0.057730674743652344,71.628079
+3710,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6071717444055001,0.441976254308694,0.057730674743652344,76.17092
+3816,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6062909567496724,0.43787425149700593,0.057791709899902344,80.84267399999999
+3922,Binary classification,Hoeffding Adaptive Tree,Bananas,0.606988013261923,0.4353242946134115,0.057852745056152344,85.696272
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+4134,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6082748608758771,0.4341139461726669,0.057913780212402344,95.89501499999999
+4240,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6105213493748526,0.4370951244459598,0.057913780212402344,101.21739399999998
+4346,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6119677790563867,0.43724966622162886,0.057974815368652344,106.75825799999998
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+4558,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6126837831906956,0.4355612408058842,0.057974815368652344,118.26167899999999
+4664,Binary classification,Hoeffding Adaptive Tree,Bananas,0.613339052112374,0.4360337816703159,0.057974815368652344,124.26691199999999
+4770,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6148039421262319,0.4352905010759299,0.0641164779663086,130.389994
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+5194,Binary classification,Hoeffding Adaptive Tree,Bananas,0.6160215674947044,0.42963386727688785,0.0642385482788086,156.525598
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+3624,Binary classification,Hoeffding Adaptive Tree,Elec2,0.875241512558653,0.8472972972972973,0.2500133514404297,22.913432999999998
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+600,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8547579298831386,0.8176100628930818,0.14198589324951172,18.498414999999998
+625,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8573717948717948,0.8172484599589321,0.14222240447998047,20.046891
+650,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8597842835130971,0.8233009708737864,0.14239025115966797,21.659211
+675,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8590504451038575,0.8263254113345521,0.14245128631591797,23.289464
+700,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8640915593705293,0.8306595365418894,0.14251232147216797,25.025232
+725,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8646408839779005,0.8344594594594595,0.14257335662841797,26.77059
+750,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8664886515353805,0.8371335504885993,0.14263439178466797,28.602532
+775,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8643410852713178,0.8330683624801273,0.14265727996826172,30.506622
+800,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8635794743429287,0.8340943683409437,0.14265727996826172,32.425334
+825,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8628640776699029,0.8345534407027819,0.14265727996826172,34.352118
+850,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8645465253239105,0.8364153627311521,0.14271831512451172,36.371837
+875,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8672768878718535,0.838888888888889,0.14271831512451172,38.48177
+900,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8665183537263627,0.8378378378378378,0.14277935028076172,40.637242
+925,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8668831168831169,0.8400520156046815,0.14277935028076172,42.878637
+950,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8661749209694415,0.8410513141426783,0.14284038543701172,45.126805999999995
+975,Binary classification,Hoeffding Adaptive Tree,Phishing,0.86652977412731,0.8414634146341464,0.14284038543701172,47.480371
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+1025,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8623046875,0.8377445339470656,0.14284038543701172,52.359728
+1050,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8636796949475691,0.8402234636871508,0.14284038543701172,54.917308999999996
+1075,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8649906890130353,0.8429035752979415,0.14284038543701172,57.530035
+1100,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8671519563239308,0.8456659619450316,0.14284038543701172,60.237019
+1125,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8701067615658363,0.8507157464212679,0.14284038543701172,62.977514
+1150,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8720626631853786,0.852852852852853,0.14290142059326172,65.816825
+1175,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8713798977853492,0.8521057786483839,0.14290142059326172,68.70086099999999
+1200,Binary classification,Hoeffding Adaptive Tree,Phishing,0.872393661384487,0.8530259365994236,0.14290142059326172,71.69850399999999
+1225,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8733660130718954,0.8541862652869238,0.14296245574951172,74.74610599999998
+1250,Binary classification,Hoeffding Adaptive Tree,Phishing,0.8742994395516414,0.8560953253895509,0.14296245574951172,77.86495099999998
+1903,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02372455596923828,1.538486
+3806,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02378559112548828,4.672632
+5709,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02384662628173828,9.280899
+7612,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02384662628173828,15.518128
+9515,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02384662628173828,23.359252
+11418,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02390766143798828,32.724381
+13321,Binary classification,Hoeffding Adaptive Tree,SMTP,1.0,0.0,0.02390766143798828,43.566998
+15224,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9992774091834724,0.0,0.03315448760986328,56.059492
+17127,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9992409202382343,0.0,0.02393054962158203,70.315874
+19030,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9993168322034789,0.0,0.02393054962158203,86.215201
+20933,Binary classification,Hoeffding Adaptive Tree,SMTP,0.999378941333843,0.0,0.02399158477783203,103.810178
+22836,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9994306984891613,0.0,0.02399158477783203,123.100461
+24739,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9994744926833212,0.0,0.02399158477783203,144.232391
+26642,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9994744942006681,0.0,0.02399158477783203,167.059054
+28545,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995095291479821,0.0,0.02399158477783203,191.625058
+30448,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995401845830459,0.0,0.02399158477783203,217.971038
+32351,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995672333848532,0.0,0.02399158477783203,246.1385
+34254,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995912766764955,0.0,0.02399158477783203,276.028821
+36157,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996127890253347,0.0,0.02399158477783203,307.727155
+38060,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996321500827662,0.0,0.02399158477783203,341.14046099999996
+39963,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996496671838246,0.0,0.02399158477783203,376.24706999999995
+41866,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996655917831124,0.0,0.02405261993408203,412.98223499999995
+43769,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996801316029976,0.0,0.02405261993408203,451.37683599999997
+45672,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996934597446958,0.0,0.02405261993408203,491.34241199999997
+47575,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9997057216126456,0.0,0.02405261993408203,532.9409959999999
+49478,Binary classification,Hoeffding Adaptive Tree,SMTP,0.99971704024092,0.0,0.02405261993408203,576.05932
+51381,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996885947839627,0.0,0.02405261993408203,620.875381
+53284,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996997166075484,0.0,0.02405261993408203,667.2134759999999
+55187,Binary classification,Hoeffding Adaptive Tree,SMTP,0.999710071394919,0.0,0.02405261993408203,715.0678459999999
+57090,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995620872672494,0.0,0.02405261993408203,764.41064
+58993,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995762137238947,0.0,0.02405261993408203,815.214443
+60896,Binary classification,Hoeffding Adaptive Tree,SMTP,0.999589457262501,0.0,0.02405261993408203,867.5634849999999
+62799,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995700500015924,0.0,0.02405261993408203,921.3075979999999
+64702,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995826957852274,0.0,0.02405261993408203,976.5012499999999
+66605,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995946189418053,0.0,0.02405261993408203,1033.066349
+68508,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9995766855941729,0.0,0.02405261993408203,1090.838953
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+74217,Binary classification,Hoeffding Adaptive Tree,SMTP,0.99960924867953,0.0,0.02405261993408203,1271.4412419999999
+76120,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996190175908775,0.0,0.02405261993408203,1333.994434
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+81829,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996455980837855,0.0,0.02405261993408203,1528.680001
+83732,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996536527689864,0.0,0.02411365509033203,1595.853878
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+87538,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996687115162731,0.0,0.02411365509033203,1733.3243249999998
+89441,Binary classification,Hoeffding Adaptive Tree,SMTP,0.9996645796064401,0.0,0.02411365509033203,1803.716354
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+106,Binary classification,Adaptive Random Forest,Bananas,0.638095238095238,0.5777777777777778,0.6023197174072266,1.25138
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+3624,Binary classification,Adaptive Random Forest,Elec2,0.8901462876069556,0.8665325285043594,5.045891761779785,149.36791399999998
+4530,Binary classification,Adaptive Random Forest,Elec2,0.8924707440936189,0.8628555336524922,6.377499580383301,220.195834
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+9060,Binary classification,Adaptive Random Forest,Elec2,0.8869632409758251,0.8668400520156047,14.3945894241333,740.068354
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+13590,Binary classification,Adaptive Random Forest,Elec2,0.8835087202884686,0.8699794661190965,22.36763858795166,1507.9316749999998
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+17214,Binary classification,Adaptive Random Forest,Elec2,0.880787776680416,0.862742474916388,9.825531959533691,2290.8714669999995
+18120,Binary classification,Adaptive Random Forest,Elec2,0.881505601854407,0.8635178946030132,13.432568550109863,2506.1422499999994
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+19932,Binary classification,Adaptive Random Forest,Elec2,0.8847022226682053,0.8666744024135531,10.915810585021973,2956.9763619999994
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+22650,Binary classification,Adaptive Random Forest,Elec2,0.8832178021104684,0.8619303648796786,11.609391212463379,3682.1047309999994
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+24462,Binary classification,Adaptive Random Forest,Elec2,0.8805854216916724,0.8573800107416631,10.653840065002441,4201.066475999999
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+26274,Binary classification,Adaptive Random Forest,Elec2,0.8801431127012522,0.8566616596112704,13.86082935333252,4746.937765999999
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+975,Binary classification,Adaptive Random Forest,Phishing,0.9045174537987679,0.8899408284023669,3.787748336791992,431.1052179999999
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+1903,Binary classification,Adaptive Random Forest,SMTP,1.0,0.0,0.17035293579101562,12.381202
+3806,Binary classification,Adaptive Random Forest,SMTP,1.0,0.0,0.17157363891601562,37.073822
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+15224,Binary classification,Adaptive Random Forest,SMTP,0.9992774091834724,0.0,0.23138427734375,404.612477
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+3922,Binary classification,Streaming Random Patches,Bananas,0.8653404743687835,0.846064139941691,7.61528205871582,2058.6755279999998
+4028,Binary classification,Streaming Random Patches,Bananas,0.8644151974174323,0.8449744463373083,7.967977523803711,2161.5792619999997
+4134,Binary classification,Streaming Random Patches,Bananas,0.8654730220179047,0.8462389380530975,7.394952774047852,2266.5958729999998
+4240,Binary classification,Streaming Random Patches,Bananas,0.8674215616890776,0.8486806677436726,7.571531295776367,2373.458397
+4346,Binary classification,Streaming Random Patches,Bananas,0.8688147295742232,0.8503937007874016,7.877435684204102,2482.305033
+4452,Binary classification,Streaming Random Patches,Bananas,0.8683441923163334,0.8496664956387892,8.180627822875977,2593.165336
+4558,Binary classification,Streaming Random Patches,Bananas,0.8689927583936801,0.8508618536097925,8.39448356628418,2705.945127
+4664,Binary classification,Streaming Random Patches,Bananas,0.8691829294445635,0.8516536964980544,8.710580825805664,2820.674173
+4770,Binary classification,Streaming Random Patches,Bananas,0.8689452715453974,0.8510131108462455,9.014997482299805,2937.453009
+4876,Binary classification,Streaming Random Patches,Bananas,0.8703589743589744,0.8523364485981308,9.167715072631836,3056.177406
+4982,Binary classification,Streaming Random Patches,Bananas,0.8713109817305762,0.8538864827900615,9.482858657836914,3176.936292
+5088,Binary classification,Streaming Random Patches,Bananas,0.8714369962649892,0.8539526574363555,9.87147331237793,3299.754349
+5194,Binary classification,Streaming Random Patches,Bananas,0.8717504332755632,0.8543944031482291,10.204122543334961,3424.594329
+5300,Binary classification,Streaming Random Patches,Bananas,0.8716739007359879,0.8542648949849978,10.538087844848633,3551.414099
+906,Binary classification,Streaming Random Patches,Elec2,0.8828729281767956,0.8811659192825113,5.258722305297852,37.408806
+1812,Binary classification,Streaming Random Patches,Elec2,0.9039204859193816,0.8804945054945055,8.443174362182617,104.985856
+2718,Binary classification,Streaming Random Patches,Elec2,0.8873757821126242,0.8602739726027397,12.445928573608398,198.51440200000002
+3624,Binary classification,Streaming Random Patches,Elec2,0.884902014904775,0.8576305906452714,16.533422470092773,314.268209
+4530,Binary classification,Streaming Random Patches,Elec2,0.8812099801280636,0.8452243958573072,19.266294479370117,451.77035
+5436,Binary classification,Streaming Random Patches,Elec2,0.8756209751609936,0.8372652864708715,24.12981605529785,609.66041
+6342,Binary classification,Streaming Random Patches,Elec2,0.8719444882510645,0.8340825500612996,28.348302841186523,788.9253299999999
+7248,Binary classification,Streaming Random Patches,Elec2,0.8691872498965089,0.8308351177730193,31.664392471313477,988.709629
+8154,Binary classification,Streaming Random Patches,Elec2,0.8690052741322213,0.8387681159420289,35.27585411071777,1209.125777
+9060,Binary classification,Streaming Random Patches,Elec2,0.869742797218236,0.844162704701532,38.39363670349121,1448.169528
+9966,Binary classification,Streaming Random Patches,Elec2,0.8681384846964375,0.8455934195064629,42.49019813537598,1706.33653
+10872,Binary classification,Streaming Random Patches,Elec2,0.8687333272008095,0.849265870920038,46.91076469421387,1983.228319
+11778,Binary classification,Streaming Random Patches,Elec2,0.8694064702386006,0.8495402073958129,41.518564224243164,2278.772125
+12684,Binary classification,Streaming Random Patches,Elec2,0.8672238429393676,0.8479320931912588,46.98099327087402,2591.81768
+13590,Binary classification,Streaming Random Patches,Elec2,0.8682758113179778,0.8513289036544851,50.757638931274414,2922.748705
+14496,Binary classification,Streaming Random Patches,Elec2,0.8687823387374957,0.8527863777089782,43.74130058288574,3269.777293
+15402,Binary classification,Streaming Random Patches,Elec2,0.8686448931887539,0.8518708354689903,49.06788444519043,3632.343799
+16308,Binary classification,Streaming Random Patches,Elec2,0.8649659655362728,0.8467427616926504,54.357858657836914,4011.129855
+17214,Binary classification,Streaming Random Patches,Elec2,0.865392435949573,0.8447987139125192,52.38222694396973,4407.893822
+18120,Binary classification,Streaming Random Patches,Elec2,0.8652795408135107,0.8448286822198208,59.36540412902832,4822.718697
+19026,Binary classification,Streaming Random Patches,Elec2,0.867700394218134,0.8459136822773186,57.10729789733887,5251.994155
+19932,Binary classification,Streaming Random Patches,Elec2,0.8692489087351363,0.84882236918436,51.34463310241699,5694.600867
+20838,Binary classification,Streaming Random Patches,Elec2,0.8691750251955656,0.8490085299656586,53.35045051574707,6149.875029
+21744,Binary classification,Streaming Random Patches,Elec2,0.8700271351699398,0.8478682170542635,59.89077186584473,6616.7506189999995
+22650,Binary classification,Streaming Random Patches,Elec2,0.8694865115457636,0.8459614382490881,65.61615180969238,7094.9355989999995
+23556,Binary classification,Streaming Random Patches,Elec2,0.868860114625345,0.8444690599667689,72.22853660583496,7585.744803
+24462,Binary classification,Streaming Random Patches,Elec2,0.8682392379706472,0.8428648042513772,80.47726249694824,8090.441156999999
+25368,Binary classification,Streaming Random Patches,Elec2,0.8672290771474751,0.8417888012025554,73.03231239318848,8608.413273
+26274,Binary classification,Streaming Random Patches,Elec2,0.8684581128915617,0.8430802760624773,79.16955757141113,9138.877569
+27180,Binary classification,Streaming Random Patches,Elec2,0.8698259685786821,0.8451234459814394,84.2670955657959,9681.232951
+28086,Binary classification,Streaming Random Patches,Elec2,0.8689335944454335,0.8434616202423985,93.53372383117676,10236.036265
+28992,Binary classification,Streaming Random Patches,Elec2,0.8688558518160808,0.8423322551215061,92.75358009338379,10801.143387
+29898,Binary classification,Streaming Random Patches,Elec2,0.8689166137070609,0.8421603769785332,90.79977607727051,11375.205452
+30804,Binary classification,Streaming Random Patches,Elec2,0.8684868356978216,0.8408063818917749,97.95510292053223,11957.401901000001
+31710,Binary classification,Streaming Random Patches,Elec2,0.8668832192752847,0.8384553561177235,105.25788688659668,12547.475367000001
+32616,Binary classification,Streaming Random Patches,Elec2,0.8664724819868159,0.8381943154374885,94.53887367248535,13145.300695000002
+33522,Binary classification,Streaming Random Patches,Elec2,0.8661436114674383,0.8380553650701988,102.01883506774902,13750.733881000002
+34428,Binary classification,Streaming Random Patches,Elec2,0.8648444534812793,0.8364441632394811,100.42782783508301,14363.910035000003
+35334,Binary classification,Streaming Random Patches,Elec2,0.8647723091727281,0.8357849876271651,107.87262153625488,14984.863075000003
+36240,Binary classification,Streaming Random Patches,Elec2,0.8642346643119292,0.83420946219167,112.83228874206543,15613.594311000003
+37146,Binary classification,Streaming Random Patches,Elec2,0.8632655808318751,0.8326689289361843,120.66686058044434,16250.422859000002
+38052,Binary classification,Streaming Random Patches,Elec2,0.8627631336889964,0.8316135689410551,126.15458106994629,16895.166705000003
+38958,Binary classification,Streaming Random Patches,Elec2,0.8634391765279668,0.8328620797989319,107.22049903869629,17548.303432000004
+39864,Binary classification,Streaming Random Patches,Elec2,0.8644356922459423,0.8353041570157259,103.5422191619873,18208.490072000004
+40770,Binary classification,Streaming Random Patches,Elec2,0.865436974171552,0.8378745788758201,97.78764533996582,18874.504490000003
+41676,Binary classification,Streaming Random Patches,Elec2,0.8666586682663467,0.8403940603728063,102.76390266418457,19545.753018000003
+42582,Binary classification,Streaming Random Patches,Elec2,0.8673821657546793,0.8415055151702265,107.51249122619629,20221.607860000004
+43488,Binary classification,Streaming Random Patches,Elec2,0.8677075907742544,0.841885392332005,102.9560489654541,20902.251232000002
+44394,Binary classification,Streaming Random Patches,Elec2,0.8679071024711104,0.8415905775568644,103.86480903625488,21587.715975000003
+45300,Binary classification,Streaming Random Patches,Elec2,0.8688933530541513,0.843053830501308,107.29028511047363,22278.011723000003
+45312,Binary classification,Streaming Random Patches,Elec2,0.8688839354682086,0.8430092751631743,107.32242012023926,22968.976341
+25,Binary classification,Streaming Random Patches,Phishing,0.8333333333333334,0.8333333333333334,0.7029104232788086,1.141902
+50,Binary classification,Streaming Random Patches,Phishing,0.8571428571428571,0.8372093023255814,0.9397382736206055,3.355867
+75,Binary classification,Streaming Random Patches,Phishing,0.8783783783783784,0.8695652173913043,0.9708013534545898,6.532426
+100,Binary classification,Streaming Random Patches,Phishing,0.8888888888888888,0.8817204301075269,1.056624412536621,10.815831
+125,Binary classification,Streaming Random Patches,Phishing,0.8790322580645161,0.8739495798319329,1.3782567977905273,16.293882
+150,Binary classification,Streaming Random Patches,Phishing,0.8791946308724832,0.8783783783783784,1.379134178161621,22.890072
+175,Binary classification,Streaming Random Patches,Phishing,0.896551724137931,0.888888888888889,1.4786596298217773,30.523139999999998
+200,Binary classification,Streaming Random Patches,Phishing,0.8944723618090452,0.8864864864864866,1.6607275009155273,39.247513
+225,Binary classification,Streaming Random Patches,Phishing,0.8973214285714286,0.8866995073891626,1.686568260192871,49.014512999999994
+250,Binary classification,Streaming Random Patches,Phishing,0.891566265060241,0.88,1.9668035507202148,59.910523
+275,Binary classification,Streaming Random Patches,Phishing,0.8905109489051095,0.8780487804878049,2.071291923522949,71.88595
+300,Binary classification,Streaming Random Patches,Phishing,0.8896321070234113,0.8754716981132077,2.2423620223999023,85.00905599999999
+325,Binary classification,Streaming Random Patches,Phishing,0.8888888888888888,0.8723404255319148,2.4750547409057617,99.14632499999999
+350,Binary classification,Streaming Random Patches,Phishing,0.8853868194842407,0.8666666666666667,2.5328550338745117,114.35437499999999
+375,Binary classification,Streaming Random Patches,Phishing,0.8850267379679144,0.8652037617554859,2.8150205612182617,130.79065599999998
+400,Binary classification,Streaming Random Patches,Phishing,0.8822055137844611,0.8613569321533923,2.795191764831543,148.41625799999997
+425,Binary classification,Streaming Random Patches,Phishing,0.8844339622641509,0.8611898016997167,2.962000846862793,167.06847699999997
+450,Binary classification,Streaming Random Patches,Phishing,0.888641425389755,0.8648648648648649,3.03415584564209,186.853211
+475,Binary classification,Streaming Random Patches,Phishing,0.890295358649789,0.8686868686868687,3.071761131286621,207.82899999999998
+500,Binary classification,Streaming Random Patches,Phishing,0.8917835671342685,0.8726415094339622,3.1551198959350586,229.951047
+525,Binary classification,Streaming Random Patches,Phishing,0.8950381679389313,0.8741418764302059,3.1928510665893555,253.214946
+550,Binary classification,Streaming Random Patches,Phishing,0.8943533697632058,0.8739130434782608,3.2878904342651367,277.566695
+575,Binary classification,Streaming Random Patches,Phishing,0.8937282229965157,0.8726513569937369,3.4417715072631836,303.140017
+600,Binary classification,Streaming Random Patches,Phishing,0.8964941569282137,0.8739837398373984,3.515273094177246,329.715755
+625,Binary classification,Streaming Random Patches,Phishing,0.8958333333333334,0.8707753479125249,3.5807180404663086,357.461609
+650,Binary classification,Streaming Random Patches,Phishing,0.8983050847457628,0.8754716981132076,3.695376396179199,386.398038
+675,Binary classification,Streaming Random Patches,Phishing,0.8961424332344213,0.8754448398576512,3.7550153732299805,416.46849299999997
+700,Binary classification,Streaming Random Patches,Phishing,0.899856938483548,0.8784722222222222,3.7909955978393555,447.643877
+725,Binary classification,Streaming Random Patches,Phishing,0.899171270718232,0.8797364085667215,3.9393529891967773,479.929216
+750,Binary classification,Streaming Random Patches,Phishing,0.9012016021361816,0.8825396825396825,3.942519187927246,513.493128
+775,Binary classification,Streaming Random Patches,Phishing,0.9018087855297158,0.8827160493827161,4.2751874923706055,548.2965389999999
+800,Binary classification,Streaming Random Patches,Phishing,0.899874843554443,0.8816568047337278,4.513812065124512,584.3583229999999
+825,Binary classification,Streaming Random Patches,Phishing,0.8992718446601942,0.8819345661450925,4.773520469665527,621.611368
+850,Binary classification,Streaming Random Patches,Phishing,0.901060070671378,0.8836565096952909,4.8153791427612305,660.1796979999999
+875,Binary classification,Streaming Random Patches,Phishing,0.902745995423341,0.884979702300406,4.980830192565918,699.8371419999999
+900,Binary classification,Streaming Random Patches,Phishing,0.9043381535038932,0.8862433862433862,5.134486198425293,740.7850809999999
+925,Binary classification,Streaming Random Patches,Phishing,0.9069264069264069,0.8903061224489796,5.209948539733887,782.8443949999998
+950,Binary classification,Streaming Random Patches,Phishing,0.9083245521601686,0.8932515337423312,5.338950157165527,826.1813729999999
+975,Binary classification,Streaming Random Patches,Phishing,0.9106776180698152,0.895808383233533,5.382990837097168,870.7373769999999
+1000,Binary classification,Streaming Random Patches,Phishing,0.9109109109109109,0.896149358226371,5.44773006439209,916.477949
+1025,Binary classification,Streaming Random Patches,Phishing,0.9111328125,0.896942242355606,5.5915327072143555,963.445117
+1050,Binary classification,Streaming Random Patches,Phishing,0.9113441372735939,0.8976897689768977,5.678961753845215,1011.481541
+1075,Binary classification,Streaming Random Patches,Phishing,0.9115456238361266,0.8986125933831376,5.788058280944824,1060.652982
+1100,Binary classification,Streaming Random Patches,Phishing,0.9117379435850773,0.8990634755463061,5.880267143249512,1110.965738
+1125,Binary classification,Streaming Random Patches,Phishing,0.9119217081850534,0.9003021148036253,6.120665550231934,1162.442095
+1150,Binary classification,Streaming Random Patches,Phishing,0.9129677980852916,0.9013806706114399,6.185591697692871,1215.0055750000001
+1175,Binary classification,Streaming Random Patches,Phishing,0.9114139693356048,0.8996138996138997,6.431841850280762,1268.8167280000002
+1200,Binary classification,Streaming Random Patches,Phishing,0.9124270225187656,0.9004739336492891,6.484606742858887,1323.7082160000002
+1225,Binary classification,Streaming Random Patches,Phishing,0.9133986928104575,0.9014869888475836,6.481654167175293,1379.6419000000003
+1250,Binary classification,Streaming Random Patches,Phishing,0.9135308246597278,0.9019963702359347,6.595587730407715,1436.6903440000003
+1903,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1670236587524414,31.246172
+3806,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1682443618774414,90.057064
+5709,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1694650650024414,168.92668600000002
+7612,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1694650650024414,266.339332
+9515,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1694650650024414,379.70068100000003
+11418,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1706857681274414,507.50093200000003
+13321,Binary classification,Streaming Random Patches,SMTP,1.0,0.0,0.1706857681274414,650.046105
+15224,Binary classification,Streaming Random Patches,SMTP,0.9992774091834724,0.0,0.2171335220336914,806.74928
+17127,Binary classification,Streaming Random Patches,SMTP,0.9992409202382343,0.0,0.1745767593383789,979.905317
+19030,Binary classification,Streaming Random Patches,SMTP,0.9993168322034789,0.0,0.1744394302368164,1169.37771
+20933,Binary classification,Streaming Random Patches,SMTP,0.999378941333843,0.0,0.17577457427978516,1374.513378
+22836,Binary classification,Streaming Random Patches,SMTP,0.9994306984891613,0.0,0.17572879791259766,1595.365052
+24739,Binary classification,Streaming Random Patches,SMTP,0.9994744926833212,0.0,0.1757516860961914,1830.5281120000002
+26642,Binary classification,Streaming Random Patches,SMTP,0.9994744942006681,0.0,0.17572879791259766,2079.072293
+28545,Binary classification,Streaming Random Patches,SMTP,0.9995095291479821,0.0,0.17572879791259766,2341.3308700000002
+30448,Binary classification,Streaming Random Patches,SMTP,0.9995401845830459,0.0,0.17563724517822266,2616.3107910000003
+32351,Binary classification,Streaming Random Patches,SMTP,0.9995672333848532,0.0,0.17577457427978516,2903.8369350000003
+34254,Binary classification,Streaming Random Patches,SMTP,0.9995912766764955,0.0,0.1756601333618164,3203.0985050000004
+36157,Binary classification,Streaming Random Patches,SMTP,0.9996127890253347,0.0,0.17568302154541016,3513.3936680000006
+38060,Binary classification,Streaming Random Patches,SMTP,0.9996321500827662,0.0,0.1757059097290039,3834.7595300000007
+39963,Binary classification,Streaming Random Patches,SMTP,0.9996496671838246,0.0,0.17577457427978516,4167.168481000001
+41866,Binary classification,Streaming Random Patches,SMTP,0.9996655917831124,0.0,0.1769266128540039,4510.027218000001
+43769,Binary classification,Streaming Random Patches,SMTP,0.9996801316029976,0.0,0.1769266128540039,4863.234695000001
+45672,Binary classification,Streaming Random Patches,SMTP,0.9996934597446958,0.0,0.1769266128540039,5226.731618000001
+47575,Binary classification,Streaming Random Patches,SMTP,0.9997057216126456,0.0,0.1770639419555664,5600.511358000001
+49478,Binary classification,Streaming Random Patches,SMTP,0.99971704024092,0.0,0.17690372467041016,5984.651066
+51381,Binary classification,Streaming Random Patches,SMTP,0.9996885947839627,0.0,0.16916751861572266,6379.477192
+53284,Binary classification,Streaming Random Patches,SMTP,0.9996997166075484,0.0,0.1770639419555664,6785.903036000001
+55187,Binary classification,Streaming Random Patches,SMTP,0.999710071394919,0.0,0.17704105377197266,7201.6518080000005
+57090,Binary classification,Streaming Random Patches,SMTP,0.9995620872672494,0.0,0.1769266128540039,7626.427031
+58993,Binary classification,Streaming Random Patches,SMTP,0.9995762137238947,0.0,0.1769266128540039,8059.133738
+60896,Binary classification,Streaming Random Patches,SMTP,0.999589457262501,0.0,0.1769723892211914,8499.283325
+62799,Binary classification,Streaming Random Patches,SMTP,0.9995700500015924,0.0,0.1769266128540039,8946.957028
+64702,Binary classification,Streaming Random Patches,SMTP,0.9995826957852274,0.0,0.17699527740478516,9401.959764000001
+66605,Binary classification,Streaming Random Patches,SMTP,0.9995946189418053,0.0,0.1769723892211914,9864.111715000001
+68508,Binary classification,Streaming Random Patches,SMTP,0.9995766855941729,0.0,0.1691446304321289,10332.853073
+70411,Binary classification,Streaming Random Patches,SMTP,0.9995881266865502,0.0,0.17690372467041016,10808.168746
+72314,Binary classification,Streaming Random Patches,SMTP,0.9995989656078437,0.0,0.16912174224853516,11290.14581
+74217,Binary classification,Streaming Random Patches,SMTP,0.99960924867953,0.0,0.1769723892211914,11778.656001
+76120,Binary classification,Streaming Random Patches,SMTP,0.9996190175908775,0.0,0.1769723892211914,12273.787996
+78023,Binary classification,Streaming Random Patches,SMTP,0.9996283099638563,0.0,0.17699527740478516,12775.472063
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+37146,Binary classification,ADWIN Bagging,Elec2,0.8245255081437609,0.7721616331096196,1.357222557067871,6182.753490999998
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+38958,Binary classification,ADWIN Bagging,Elec2,0.8233950252842878,0.7698534823041413,1.147334098815918,6708.424011999998
+39864,Binary classification,ADWIN Bagging,Elec2,0.8222160901086221,0.7699250073044834,0.7468709945678711,6977.570913999998
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+41676,Binary classification,ADWIN Bagging,Elec2,0.8235872825434913,0.7755388654820785,1.097620964050293,7528.4976689999985
+42582,Binary classification,ADWIN Bagging,Elec2,0.8245696437378174,0.7776785714285713,1.5453977584838867,7809.843107999998
+43488,Binary classification,ADWIN Bagging,Elec2,0.8251431462276082,0.7787605469886529,0.8941831588745117,8094.859004999998
+44394,Binary classification,ADWIN Bagging,Elec2,0.8243867276372401,0.7766701042740918,0.744959831237793,8383.886548999999
+45300,Binary classification,ADWIN Bagging,Elec2,0.823770944170953,0.7766305716444221,0.5983161926269531,8676.996437
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+200,Binary classification,ADWIN Bagging,Phishing,0.8592964824120602,0.8510638297872339,0.6653299331665039,15.477702
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+475,Binary classification,ADWIN Bagging,Phishing,0.869198312236287,0.8402061855670103,0.859832763671875,85.340536
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+525,Binary classification,ADWIN Bagging,Phishing,0.8683206106870229,0.8384074941451991,0.8598556518554688,103.968058
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+575,Binary classification,ADWIN Bagging,Phishing,0.867595818815331,0.8382978723404255,0.8599014282226562,124.33795699999999
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+625,Binary classification,ADWIN Bagging,Phishing,0.8717948717948718,0.8373983739837398,0.8966064453125,146.56138699999997
+650,Binary classification,ADWIN Bagging,Phishing,0.8767334360554699,0.846153846153846,0.897308349609375,158.32837399999997
+675,Binary classification,ADWIN Bagging,Phishing,0.8753709198813057,0.8478260869565216,0.92486572265625,170.52005599999995
+700,Binary classification,ADWIN Bagging,Phishing,0.8798283261802575,0.8515901060070671,0.8633918762207031,183.10001399999996
+725,Binary classification,ADWIN Bagging,Phishing,0.8825966850828729,0.8576214405360134,0.9612770080566406,196.14419299999997
+750,Binary classification,ADWIN Bagging,Phishing,0.8865153538050734,0.8631239935587761,0.9975471496582031,209.59830599999998
+775,Binary classification,ADWIN Bagging,Phishing,0.8875968992248062,0.863849765258216,1.0525703430175781,223.56014999999996
+800,Binary classification,ADWIN Bagging,Phishing,0.8873591989987485,0.8652694610778443,1.1531257629394531,237.94997899999996
+825,Binary classification,ADWIN Bagging,Phishing,0.8871359223300971,0.8661870503597122,1.1537437438964844,252.78040299999995
+850,Binary classification,ADWIN Bagging,Phishing,0.8881036513545347,0.8671328671328671,1.1632118225097656,267.983484
+875,Binary classification,ADWIN Bagging,Phishing,0.8901601830663616,0.8688524590163934,1.1906776428222656,283.60495299999997
+900,Binary classification,ADWIN Bagging,Phishing,0.8887652947719689,0.8670212765957446,1.2457008361816406,299.65263899999997
+925,Binary classification,ADWIN Bagging,Phishing,0.8896103896103896,0.8695652173913043,1.2457923889160156,316.05876399999994
+950,Binary classification,ADWIN Bagging,Phishing,0.8893572181243414,0.8708487084870848,1.2458381652832031,332.97263699999996
+975,Binary classification,ADWIN Bagging,Phishing,0.8901437371663244,0.8718562874251498,1.2458839416503906,350.27117
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+1025,Binary classification,ADWIN Bagging,Phishing,0.8876953125,0.8700564971751412,1.2459068298339844,386.172169
+1050,Binary classification,ADWIN Bagging,Phishing,0.8894184938036225,0.8725274725274725,1.2458839416503906,404.74234
+1075,Binary classification,ADWIN Bagging,Phishing,0.8901303538175046,0.8742004264392325,1.2458839416503906,423.71995200000003
+1100,Binary classification,ADWIN Bagging,Phishing,0.89171974522293,0.8761706555671176,1.2458839416503906,443.13918
+1125,Binary classification,ADWIN Bagging,Phishing,0.8932384341637011,0.8790322580645162,1.2458839416503906,462.95518100000004
+1150,Binary classification,ADWIN Bagging,Phishing,0.8938207136640557,0.8794466403162056,1.2458839416503906,483.090208
+1175,Binary classification,ADWIN Bagging,Phishing,0.8926746166950597,0.877906976744186,1.2458839416503906,503.74833900000004
+1200,Binary classification,ADWIN Bagging,Phishing,0.8932443703085905,0.8783269961977186,1.2550315856933594,524.8299360000001
+1225,Binary classification,ADWIN Bagging,Phishing,0.8929738562091504,0.8779123951537745,1.3099861145019531,546.3067460000001
+1250,Binary classification,ADWIN Bagging,Phishing,0.8935148118494796,0.8792007266121706,1.3100776672363281,568.2182720000001
+1903,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.15993690490722656,9.565839
+3806,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.16054725646972656,28.660555
+5709,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.1610889434814453,57.169533
+7612,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.16111183166503906,95.02592100000001
+9515,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.16111183166503906,141.315828
+11418,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.16172218322753906,195.517174
+13321,Binary classification,ADWIN Bagging,SMTP,1.0,0.0,0.1617450714111328,256.578558
+15224,Binary classification,ADWIN Bagging,SMTP,0.9992774091834724,0.0,0.2173633575439453,324.084886
+17127,Binary classification,ADWIN Bagging,SMTP,0.9992409202382343,0.0,0.16245460510253906,398.342181
+19030,Binary classification,ADWIN Bagging,SMTP,0.9993168322034789,0.0,0.16227149963378906,479.30544
+20933,Binary classification,ADWIN Bagging,SMTP,0.999378941333843,0.0,0.1629047393798828,566.848605
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+26642,Binary classification,ADWIN Bagging,SMTP,0.9994744942006681,0.0,0.1628131866455078,867.1613560000001
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+30448,Binary classification,ADWIN Bagging,SMTP,0.9995401845830459,0.0,0.16292762756347656,1094.7710920000002
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+3392,Binary classification,AdaBoost,Bananas,0.6234149218519611,0.5931825422108953,0.2317180633544922,360.725819
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+3816,Binary classification,AdaBoost,Bananas,0.6277850589777195,0.5970488081725313,0.32617759704589844,455.49479399999996
+3922,Binary classification,AdaBoost,Bananas,0.6322366743177761,0.6009961261759823,0.35390281677246094,480.941019
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+4982,Binary classification,AdaBoost,Bananas,0.6707488456133307,0.6378091872791519,0.44574546813964844,774.746403
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+5194,Binary classification,AdaBoost,Bananas,0.674369343346813,0.6412051771695311,0.4518413543701172,841.965614
+5300,Binary classification,AdaBoost,Bananas,0.6778637478769579,0.64504054897068,0.4531536102294922,876.7139659999999
+906,Binary classification,AdaBoost,Elec2,0.9337016574585635,0.933184855233853,1.423478126525879,13.145088
+1812,Binary classification,AdaBoost,Elec2,0.9491993373826615,0.9378378378378379,2.051041603088379,36.742593
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+5436,Binary classification,AdaBoost,Elec2,0.9332106715731371,0.9144876325088339,3.582810401916504,253.628197
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+5300,Binary classification,Bagging,Bananas,0.6340819022457067,0.4594368553108447,0.7031240463256836,1170.8531239999998
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+625,Binary classification,Leveraging Bagging,Phishing,0.8782051282051282,0.8442622950819672,2.352017402648926,424.555734
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+1903,Binary classification,Leveraging Bagging,SMTP,1.0,0.0,0.16020870208740234,31.58816
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+906,Binary classification,Voting,Elec2,0.8795580110497238,0.880351262349067,4.715929985046387,35.551681
+1812,Binary classification,Voting,Elec2,0.8807288790723358,0.8536585365853658,4.9170331954956055,87.613259
+2718,Binary classification,Voting,Elec2,0.8689731321310269,0.8344186046511628,4.988085746765137,154.923184
+3624,Binary classification,Voting,Elec2,0.8793817278498481,0.8493622888659084,4.879870414733887,235.92708
+4530,Binary classification,Voting,Elec2,0.8792227864870833,0.8405712620227338,5.017077445983887,328.79801
+5436,Binary classification,Voting,Elec2,0.8689972401103956,0.8260869565217391,4.985064506530762,432.967134
+6342,Binary classification,Voting,Elec2,0.8680018924459865,0.8269588587967748,4.949084281921387,548.642546
+7248,Binary classification,Voting,Elec2,0.8643576652407893,0.8194010655888295,4.962946891784668,674.769885
+8154,Binary classification,Voting,Elec2,0.8671654605666625,0.8317016317016317,5.020190238952637,811.067026
+9060,Binary classification,Voting,Elec2,0.8711778341980351,0.8417627118644068,5.0752363204956055,957.595858
+9966,Binary classification,Voting,Elec2,0.8706472654290015,0.845165165165165,4.979113578796387,1113.746382
+10872,Binary classification,Voting,Elec2,0.8737006715113605,0.8516156922079325,4.9885969161987305,1279.290866
+11778,Binary classification,Voting,Elec2,0.8733972998216863,0.8507059176930009,5.106616020202637,1454.661274
+12684,Binary classification,Voting,Elec2,0.873294961759836,0.8513551012857274,5.2120466232299805,1640.606202
+13590,Binary classification,Voting,Elec2,0.8755611156082125,0.8560973534167304,5.144991874694824,1836.8358979999998
+14496,Binary classification,Voting,Elec2,0.8765781303897896,0.8583643416989946,5.178118705749512,2042.985996
+15402,Binary classification,Voting,Elec2,0.8766963184208818,0.8575500712624708,5.108157157897949,2257.366998
+16308,Binary classification,Voting,Elec2,0.8711596247010487,0.8493366798135532,5.1558027267456055,2480.0447249999997
+17214,Binary classification,Voting,Elec2,0.8687038865973392,0.8429683157309616,5.140070915222168,2710.925816
+18120,Binary classification,Voting,Elec2,0.8689773166289531,0.8433623647400369,5.172907829284668,2950.660411
+19026,Binary classification,Voting,Elec2,0.8696977660972405,0.8421320766732471,5.328249931335449,3199.829749
+19932,Binary classification,Voting,Elec2,0.8659876574180925,0.8380132209351688,5.355593681335449,3457.907085
+20838,Binary classification,Voting,Elec2,0.8617843259586313,0.8322851153039832,5.442904472351074,3724.5720149999997
+21744,Binary classification,Voting,Elec2,0.862668445016787,0.8307064293003741,5.347712516784668,3998.8413929999997
+22650,Binary classification,Voting,Elec2,0.8610093160845953,0.8268045774647886,5.363558769226074,4280.436632
+23556,Binary classification,Voting,Elec2,0.85434090426661,0.8163571160948456,5.3763532638549805,4569.013267
+24462,Binary classification,Voting,Elec2,0.8534401700666366,0.8138145936120489,5.330439567565918,4864.708005
+25368,Binary classification,Voting,Elec2,0.8518941932431899,0.8121030257564391,5.456484794616699,5167.517117
+26274,Binary classification,Voting,Elec2,0.8530811098846725,0.8130931628897928,5.321070671081543,5477.642376000001
+27180,Binary classification,Voting,Elec2,0.8524964126715479,0.8125672074430782,5.426630973815918,5794.594214000001
+28086,Binary classification,Voting,Elec2,0.8496350364963504,0.8078795323233702,5.3666486740112305,6118.251751000001
+28992,Binary classification,Voting,Elec2,0.8475043979165948,0.8032575319300432,5.4148359298706055,6448.591708000001
+29898,Binary classification,Voting,Elec2,0.8460046158477439,0.8002429711905589,5.3892927169799805,6785.693940000001
+30804,Binary classification,Voting,Elec2,0.8462162776352953,0.7992881657556884,5.532000541687012,7130.317230000001
+31710,Binary classification,Voting,Elec2,0.8429783342268756,0.7938387644403958,5.507189750671387,7481.445887000001
+32616,Binary classification,Voting,Elec2,0.8419745515866932,0.7926122646064703,5.485476493835449,7839.281994000001
+33522,Binary classification,Voting,Elec2,0.8421884788639957,0.7931492922499414,5.629275321960449,8203.623919000001
+34428,Binary classification,Voting,Elec2,0.8400092950300636,0.7894656371837016,5.587969779968262,8574.868737
+35334,Binary classification,Voting,Elec2,0.8398947159878867,0.7879287722586691,5.669405937194824,8954.118864
+36240,Binary classification,Voting,Elec2,0.8408896492728828,0.7879523389232127,5.650286674499512,9340.118817
+37146,Binary classification,Voting,Elec2,0.8397092475434109,0.7854569040069184,5.6525373458862305,9731.872155000001
+38052,Binary classification,Voting,Elec2,0.8398202412551575,0.7854402083993381,5.638819694519043,10129.488521000001
+38958,Binary classification,Voting,Elec2,0.8406704828400544,0.787685992816829,5.6699628829956055,10532.813227
+39864,Binary classification,Voting,Elec2,0.841381732433585,0.7910235647949235,5.623560905456543,10941.028498
+40770,Binary classification,Voting,Elec2,0.8422085408030612,0.7943480067772769,5.627467155456543,11353.937417
+41676,Binary classification,Voting,Elec2,0.8431673665266947,0.7973835947671896,5.641619682312012,11771.547133999999
+42582,Binary classification,Voting,Elec2,0.8438505436697118,0.7987529888919157,5.640711784362793,12193.871152999998
+43488,Binary classification,Voting,Elec2,0.843999356129418,0.7991592160577892,5.725451469421387,12620.815871999997
+44394,Binary classification,Voting,Elec2,0.8432635775910616,0.7972256221950225,5.7456769943237305,13052.460535999997
+45300,Binary classification,Voting,Elec2,0.8436830835117773,0.7980031379261162,5.7547407150268555,13488.904282999996
+45312,Binary classification,Voting,Elec2,0.8436803425216834,0.7979576118892089,5.757502555847168,13925.545040999996
+25,Binary classification,Voting,Phishing,0.5833333333333334,0.7058823529411764,0.17400836944580078,0.162813
+50,Binary classification,Voting,Phishing,0.7346938775510204,0.7636363636363637,0.20249652862548828,0.520257
+75,Binary classification,Voting,Phishing,0.7837837837837838,0.8048780487804877,0.23151493072509766,1.0500919999999998
+100,Binary classification,Voting,Phishing,0.8080808080808081,0.819047619047619,0.26002979278564453,1.7634529999999997
+125,Binary classification,Voting,Phishing,0.8145161290322581,0.8217054263565893,0.2885446548461914,2.7650449999999998
+150,Binary classification,Voting,Phishing,0.8187919463087249,0.830188679245283,0.3175630569458008,4.083864999999999
+175,Binary classification,Voting,Phishing,0.8390804597701149,0.8390804597701148,0.34607791900634766,5.803779
+200,Binary classification,Voting,Phishing,0.8391959798994975,0.8383838383838383,0.3750925064086914,7.866028
+225,Binary classification,Voting,Phishing,0.8348214285714286,0.8294930875576038,0.4036073684692383,10.317012
+250,Binary classification,Voting,Phishing,0.8313253012048193,0.8264462809917356,0.43212223052978516,13.231482
+275,Binary classification,Voting,Phishing,0.8357664233576643,0.8288973384030419,0.46164798736572266,16.680039999999998
+300,Binary classification,Voting,Phishing,0.842809364548495,0.8327402135231317,0.49016284942626953,20.639260999999998
+325,Binary classification,Voting,Phishing,0.8549382716049383,0.8417508417508418,0.5191812515258789,25.174847
+350,Binary classification,Voting,Phishing,0.8624641833810889,0.8471337579617835,0.5476961135864258,30.349829
+375,Binary classification,Voting,Phishing,0.8609625668449198,0.8433734939759037,0.5762109756469727,36.11991
+400,Binary classification,Voting,Phishing,0.8621553884711779,0.8424068767908309,0.605229377746582,42.598397999999996
+425,Binary classification,Voting,Phishing,0.8632075471698113,0.839779005524862,0.6337442398071289,49.849208
+450,Binary classification,Voting,Phishing,0.8663697104677061,0.8412698412698413,0.6627893447875977,57.823257999999996
+475,Binary classification,Voting,Phishing,0.8649789029535865,0.8407960199004976,0.6913042068481445,66.560459
+500,Binary classification,Voting,Phishing,0.8657314629258517,0.8445475638051043,2.87209415435791,96.81871699999999
+525,Binary classification,Voting,Phishing,0.8683206106870229,0.8442437923250564,2.980504035949707,127.96343099999999
+550,Binary classification,Voting,Phishing,0.8688524590163934,0.8461538461538463,3.08364200592041,159.97764899999999
+575,Binary classification,Voting,Phishing,0.8710801393728222,0.848360655737705,3.1883134841918945,192.90880399999998
+600,Binary classification,Voting,Phishing,0.8747913188647746,0.8502994011976048,3.300492286682129,226.71997
+625,Binary classification,Voting,Phishing,0.8733974358974359,0.8460038986354775,3.412938117980957,261.370264
+650,Binary classification,Voting,Phishing,0.8767334360554699,0.8523985239852399,3.522160530090332,296.927054
+675,Binary classification,Voting,Phishing,0.8783382789317508,0.8571428571428572,3.6335840225219727,333.391974
+700,Binary classification,Voting,Phishing,0.882689556509299,0.8605442176870748,3.7482118606567383,370.807982
+725,Binary classification,Voting,Phishing,0.8839779005524862,0.864516129032258,3.8615503311157227,409.129822
+750,Binary classification,Voting,Phishing,0.8851802403204272,0.8664596273291927,3.975522041320801,448.34317699999997
+775,Binary classification,Voting,Phishing,0.8863049095607235,0.8670694864048338,4.095002174377441,488.481904
+800,Binary classification,Voting,Phishing,0.886107634543179,0.8683068017366136,4.146827697753906,529.573688
+825,Binary classification,Voting,Phishing,0.8859223300970874,0.8690807799442897,4.390903472900391,571.6173799999999
+850,Binary classification,Voting,Phishing,0.8869257950530035,0.8695652173913044,4.504707336425781,614.6492939999999
+875,Binary classification,Voting,Phishing,0.8890160183066361,0.8711819389110226,4.624469757080078,658.6172529999999
+900,Binary classification,Voting,Phishing,0.8876529477196885,0.869340232858991,4.741554260253906,703.5317429999999
+925,Binary classification,Voting,Phishing,0.8896103896103896,0.8728179551122195,4.862430572509766,749.5245539999999
+950,Binary classification,Voting,Phishing,0.8904109589041096,0.8752997601918464,4.984291076660156,796.5006999999998
+975,Binary classification,Voting,Phishing,0.8921971252566735,0.8771929824561404,5.102375030517578,844.5149469999998
+1000,Binary classification,Voting,Phishing,0.8928928928928929,0.8779931584948689,5.219093322753906,893.5084249999998
+1025,Binary classification,Voting,Phishing,0.892578125,0.8780487804878048,5.178688049316406,943.5715689999997
+1050,Binary classification,Voting,Phishing,0.894184938036225,0.8802588996763754,5.151969909667969,994.6247309999998
+1075,Binary classification,Voting,Phishing,0.8929236499068901,0.8798328108672936,5.117225646972656,1046.6512989999997
+1100,Binary classification,Voting,Phishing,0.8944494995450409,0.8816326530612245,5.075950622558594,1099.6701919999996
+1125,Binary classification,Voting,Phishing,0.8959074733096085,0.884272997032641,5.007194519042969,1153.6019869999996
+1150,Binary classification,Voting,Phishing,0.896431679721497,0.8845780795344327,4.982025146484375,1208.4750359999996
+1175,Binary classification,Voting,Phishing,0.8952299829642248,0.8829686013320648,4.96966552734375,1264.1689839999997
+1200,Binary classification,Voting,Phishing,0.896580483736447,0.8841121495327102,4.9371490478515625,1320.7795169999997
+1225,Binary classification,Voting,Phishing,0.8970588235294118,0.8844036697247706,4.8813018798828125,1378.3046599999998
+1250,Binary classification,Voting,Phishing,0.8967173738991193,0.8845120859444942,4.820304870605469,1436.7224909999998
+1903,Binary classification,Voting,SMTP,1.0,0.0,4.661611557006836,43.527964
+3806,Binary classification,Voting,SMTP,1.0,0.0,4.557134628295898,113.03314999999999
+5709,Binary classification,Voting,SMTP,1.0,0.0,4.496244430541992,201.747221
+7612,Binary classification,Voting,SMTP,1.0,0.0,4.508665084838867,310.754596
+9515,Binary classification,Voting,SMTP,1.0,0.0,4.565656661987305,436.825284
+11418,Binary classification,Voting,SMTP,1.0,0.0,4.554738998413086,579.964386
+13321,Binary classification,Voting,SMTP,1.0,0.0,4.492513656616211,739.485002
+15224,Binary classification,Voting,SMTP,0.9997372397030808,0.7777777777777778,4.532373428344727,915.25293
+17127,Binary classification,Voting,SMTP,0.9997664369963798,0.8181818181818181,4.528841018676758,1107.42481
+19030,Binary classification,Voting,SMTP,0.9997897945241474,0.8181818181818181,4.520586013793945,1314.036215
+20933,Binary classification,Voting,SMTP,0.9998089050257978,0.8181818181818181,4.519166946411133,1534.1862760000001
+22836,Binary classification,Voting,SMTP,0.9998248303043573,0.8181818181818181,4.512857437133789,1768.1243410000002
+24739,Binary classification,Voting,SMTP,0.9998383054410219,0.8181818181818181,4.568696975708008,2014.7470960000003
+26642,Binary classification,Voting,SMTP,0.9998123193573815,0.782608695652174,4.55253791809082,2273.6909760000003
+28545,Binary classification,Voting,SMTP,0.9998248318385651,0.782608695652174,4.554193496704102,2543.9053730000005
+30448,Binary classification,Voting,SMTP,0.9998357802082307,0.782608695652174,4.487833023071289,2824.6447140000005
+32351,Binary classification,Voting,SMTP,0.9998454404945905,0.782608695652174,4.52525520324707,3116.2234200000003
+34254,Binary classification,Voting,SMTP,0.9998540273844627,0.782608695652174,4.608850479125977,3418.6303260000004
+36157,Binary classification,Voting,SMTP,0.999861710366191,0.782608695652174,4.462549209594727,3731.2161630000005
+38060,Binary classification,Voting,SMTP,0.9998686250295594,0.782608695652174,4.517663955688477,4053.8854360000005
+39963,Binary classification,Voting,SMTP,0.9998748811370802,0.782608695652174,4.596040725708008,4386.480402
+41866,Binary classification,Voting,SMTP,0.9998805684939687,0.782608695652174,4.581964492797852,4729.507439
+43769,Binary classification,Voting,SMTP,0.9998857612867849,0.782608695652174,4.56077766418457,5082.623411
+45672,Binary classification,Voting,SMTP,0.9998905213373913,0.782608695652174,4.554697036743164,5446.283888999999
+47575,Binary classification,Voting,SMTP,0.9998949005759449,0.782608695652174,4.589784622192383,5821.612630999999
+49478,Binary classification,Voting,SMTP,0.9998989429431857,0.782608695652174,4.514947891235352,6206.523862999999
+51381,Binary classification,Voting,SMTP,0.9998637602179836,0.72,4.571069717407227,6600.877267999999
+53284,Binary classification,Voting,SMTP,0.9998686260158024,0.72,4.544900894165039,7002.824473
+55187,Binary classification,Voting,SMTP,0.9998731562352771,0.72,4.490015029907227,7412.266105
+57090,Binary classification,Voting,SMTP,0.9997197358510396,0.5294117647058824,4.520219802856445,7829.0322129999995
+58993,Binary classification,Voting,SMTP,0.9997287767832926,0.5294117647058824,4.567926406860352,8253.169596
+60896,Binary classification,Voting,SMTP,0.9997372526480006,0.5294117647058824,4.602060317993164,8684.574786
+62799,Binary classification,Voting,SMTP,0.9997133666677283,0.5,4.518564224243164,9122.220249
+64702,Binary classification,Voting,SMTP,0.9997217971901516,0.5,4.562410354614258,9566.245368
+66605,Binary classification,Voting,SMTP,0.9997297459612036,0.5,4.587350845336914,10016.770375
+68508,Binary classification,Voting,SMTP,0.9997226560789408,0.5128205128205129,4.58268928527832,10473.685786
+70411,Binary classification,Voting,SMTP,0.9997301519670502,0.5128205128205129,4.552003860473633,10937.213874000001
+72314,Binary classification,Voting,SMTP,0.9997372533292769,0.5128205128205129,4.568490982055664,11407.187031000001
+74217,Binary classification,Voting,SMTP,0.9997439905141748,0.5128205128205129,4.501398086547852,11883.434676
+76120,Binary classification,Voting,SMTP,0.9997503908354025,0.5128205128205129,4.530572891235352,12366.124718000001
+78023,Binary classification,Voting,SMTP,0.999756478941837,0.5128205128205129,4.565195083618164,12855.350972
+79926,Binary classification,Voting,SMTP,0.9997622771348139,0.5128205128205129,4.555276870727539,13350.750206
+81829,Binary classification,Voting,SMTP,0.9997678056411008,0.5128205128205129,4.523683547973633,13852.638924
+83732,Binary classification,Voting,SMTP,0.9997730828486463,0.5128205128205129,4.51640510559082,14360.452684
+85635,Binary classification,Voting,SMTP,0.9997781255108952,0.5128205128205129,4.554742813110352,14874.156807
+87538,Binary classification,Voting,SMTP,0.9997829489244549,0.5128205128205129,4.55351448059082,15393.589182
+89441,Binary classification,Voting,SMTP,0.9997763864042933,0.5,4.576028823852539,15919.905447
+91344,Binary classification,Voting,SMTP,0.9997700973254655,0.4878048780487804,4.509759902954102,16451.368555
+93247,Binary classification,Voting,SMTP,0.9997747892671,0.4878048780487804,4.633722305297852,16987.639193000003
+95150,Binary classification,Voting,SMTP,0.9997792935290964,0.4878048780487804,4.606340408325195,17528.67073
+95156,Binary classification,Voting,SMTP,0.9997793074457464,0.4878048780487804,4.602045059204102,18069.786262
+106,Binary classification,[baseline] Last Class,Bananas,0.5333333333333333,0.5242718446601942,0.0005102157592773438,0.004468
+212,Binary classification,[baseline] Last Class,Bananas,0.5876777251184834,0.5538461538461539,0.0005102157592773438,0.067972
+318,Binary classification,[baseline] Last Class,Bananas,0.5457413249211357,0.5102040816326531,0.0005102157592773438,0.134988
+424,Binary classification,[baseline] Last Class,Bananas,0.5460992907801419,0.5025906735751295,0.0005102157592773438,0.20522
+530,Binary classification,[baseline] Last Class,Bananas,0.5671077504725898,0.5096359743040686,0.0005102157592773438,0.337716
+636,Binary classification,[baseline] Last Class,Bananas,0.5464566929133858,0.4875444839857651,0.0005102157592773438,0.474055
+742,Binary classification,[baseline] Last Class,Bananas,0.5573549257759784,0.4875,0.0005102157592773438,0.646583
+848,Binary classification,[baseline] Last Class,Bananas,0.5501770956316411,0.4816326530612245,0.0005102157592773438,0.822555
+954,Binary classification,[baseline] Last Class,Bananas,0.5487932843651626,0.4794188861985472,0.0005102157592773438,1.00209
+1060,Binary classification,[baseline] Last Class,Bananas,0.5448536355051936,0.46799116997792495,0.0005102157592773438,1.292978
+1166,Binary classification,[baseline] Last Class,Bananas,0.534763948497854,0.4590818363273453,0.0005102157592773438,1.5875979999999998
+1272,Binary classification,[baseline] Last Class,Bananas,0.5287175452399685,0.456935630099728,0.0005102157592773438,1.885535
+1378,Binary classification,[baseline] Last Class,Bananas,0.5286855482933914,0.45232067510548524,0.0005102157592773438,2.211477
+1484,Binary classification,[baseline] Last Class,Bananas,0.5252865812542145,0.44913928012519555,0.0005102157592773438,2.547239
+1590,Binary classification,[baseline] Last Class,Bananas,0.5204531151667715,0.4437956204379563,0.0005102157592773438,2.88734
+1696,Binary classification,[baseline] Last Class,Bananas,0.5227138643067847,0.4455106237148732,0.0005102157592773438,3.258534
+1802,Binary classification,[baseline] Last Class,Bananas,0.524153248195447,0.4523961661341854,0.0005102157592773438,3.633124
+1908,Binary classification,[baseline] Last Class,Bananas,0.5233350812794966,0.456664674237896,0.0005102157592773438,4.01125
+2014,Binary classification,[baseline] Last Class,Bananas,0.5171385991058122,0.4563758389261745,0.0005102157592773438,4.505139000000001
+2120,Binary classification,[baseline] Last Class,Bananas,0.5143935818782445,0.45813586097946285,0.0005102157592773438,5.002779
+2226,Binary classification,[baseline] Last Class,Bananas,0.5114606741573033,0.45459106874059213,0.0005102157592773438,5.503925000000001
+2332,Binary classification,[baseline] Last Class,Bananas,0.510939510939511,0.45506692160611856,0.0005102157592773438,6.074663000000001
+2438,Binary classification,[baseline] Last Class,Bananas,0.5104636848584325,0.4530032095369097,0.0005102157592773438,6.648598000000001
+2544,Binary classification,[baseline] Last Class,Bananas,0.5084545812033032,0.45462478184991273,0.0005102157592773438,7.226634000000001
+2650,Binary classification,[baseline] Last Class,Bananas,0.5096262740656852,0.458072590738423,0.0005102157592773438,7.8632990000000005
+2756,Binary classification,[baseline] Last Class,Bananas,0.5092558983666061,0.45746388443017655,0.0005102157592773438,8.503527
+2862,Binary classification,[baseline] Last Class,Bananas,0.5103110800419434,0.4563445867287544,0.0005102157592773438,9.147193
+2968,Binary classification,[baseline] Last Class,Bananas,0.5133131108864173,0.457957957957958,0.0005102157592773438,9.82546
+3074,Binary classification,[baseline] Last Class,Bananas,0.5099251545720794,0.4563176895306859,0.0005102157592773438,10.507099
+3180,Binary classification,[baseline] Last Class,Bananas,0.5102233406731677,0.45387583304103823,0.0005102157592773438,11.191893
+3286,Binary classification,[baseline] Last Class,Bananas,0.5095890410958904,0.45222713362801764,0.0005102157592773438,11.975438
+3392,Binary classification,[baseline] Last Class,Bananas,0.5107637864936597,0.4558871761233191,0.0005102157592773438,12.764918
+3498,Binary classification,[baseline] Last Class,Bananas,0.5124392336288247,0.45579316948611553,0.0005102157592773438,13.557573
+3604,Binary classification,[baseline] Last Class,Bananas,0.5134610047182903,0.45440398381574854,0.0005102157592773438,14.3795
+3710,Binary classification,[baseline] Last Class,Bananas,0.5122674575357239,0.4546276756104914,0.0005102157592773438,15.204998
+3816,Binary classification,[baseline] Last Class,Bananas,0.510615989515072,0.4536142815335089,0.0005102157592773438,16.116361
+3922,Binary classification,[baseline] Last Class,Bananas,0.5090538128028564,0.45078459343794575,0.0005102157592773438,17.035489000000002
+4028,Binary classification,[baseline] Last Class,Bananas,0.5108020859200397,0.45247359644246804,0.0005102157592773438,17.958008000000003
+4134,Binary classification,[baseline] Last Class,Bananas,0.5102830873457537,0.4517876489707476,0.0005102157592773438,18.927027000000002
+4240,Binary classification,[baseline] Last Class,Bananas,0.5102618542108988,0.4525316455696203,0.0005102157592773438,19.900154000000004
+4346,Binary classification,[baseline] Last Class,Bananas,0.5074798619102416,0.4490216271884655,0.0005102157592773438,20.876623000000006
+4452,Binary classification,[baseline] Last Class,Bananas,0.5099977533138621,0.45132075471698113,0.0005102157592773438,21.913356000000007
+4558,Binary classification,[baseline] Last Class,Bananas,0.5099846390168971,0.45390070921985815,0.0005102157592773438,22.953869000000008
+4664,Binary classification,[baseline] Last Class,Bananas,0.5099721209521767,0.4553039332538737,0.0005102157592773438,23.99911400000001
+4770,Binary classification,[baseline] Last Class,Bananas,0.5110085971901867,0.4556489262371615,0.0005102157592773438,25.08372100000001
+4876,Binary classification,[baseline] Last Class,Bananas,0.5109743589743589,0.4539624370132845,0.0005102157592773438,26.17171900000001
+4982,Binary classification,[baseline] Last Class,Bananas,0.5099377635013049,0.45379279480868207,0.0005102157592773438,27.26320500000001
+5088,Binary classification,[baseline] Last Class,Bananas,0.5099272655789266,0.45364891518737677,0.0005102157592773438,28.44143600000001
+5194,Binary classification,[baseline] Last Class,Bananas,0.5097246293086848,0.4531786941580756,0.0005102157592773438,29.62357400000001
+5300,Binary classification,[baseline] Last Class,Bananas,0.5095301000188714,0.4529572721532309,0.0005102157592773438,30.80903600000001
+906,Binary classification,[baseline] Last Class,Elec2,0.8530386740331491,0.8500563697857948,0.0005102157592773438,0.224121
+1812,Binary classification,[baseline] Last Class,Elec2,0.8619547211485368,0.8287671232876712,0.0005102157592773438,0.785464
+2718,Binary classification,[baseline] Last Class,Elec2,0.8450496871549503,0.80958842152872,0.0005102157592773438,1.64751
+3624,Binary classification,[baseline] Last Class,Elec2,0.8418437758763456,0.8056968463886063,0.0005102157592773438,2.8059529999999997
+4530,Binary classification,[baseline] Last Class,Elec2,0.8388165157871494,0.7960893854748604,0.0005102157592773438,4.158177
+5436,Binary classification,[baseline] Last Class,Elec2,0.8413983440662374,0.7995348837209302,0.0005102157592773438,5.857693
+6342,Binary classification,[baseline] Last Class,Elec2,0.8370919413341744,0.7958094485076103,0.0005102157592773438,7.811494
+7248,Binary classification,[baseline] Last Class,Elec2,0.8359321098385539,0.7948231233822259,0.0005102157592773438,10.005109
+8154,Binary classification,[baseline] Last Class,Elec2,0.8352753587636453,0.8021799970540581,0.0005102157592773438,12.510532
+9060,Binary classification,[baseline] Last Class,Elec2,0.8358538470029805,0.8069081937410726,0.0005102157592773438,15.278307999999999
+9966,Binary classification,[baseline] Last Class,Elec2,0.8372303060712494,0.8118765947575969,0.0005102157592773438,18.289258999999998
+10872,Binary classification,[baseline] Last Class,Elec2,0.8368135406126391,0.8140461215932915,0.0005102157592773438,21.565545999999998
+11778,Binary classification,[baseline] Last Class,Elec2,0.8374798335739153,0.8150724637681159,0.0005102157592773438,25.041396
+12684,Binary classification,[baseline] Last Class,Elec2,0.8384451628163684,0.8161177420802298,0.0005102157592773438,28.814916
+13590,Binary classification,[baseline] Last Class,Elec2,0.842004562513798,0.8223417459660736,0.0005102157592773438,32.85712
+14496,Binary classification,[baseline] Last Class,Elec2,0.8448430493273542,0.8264794383149447,0.0005102157592773438,37.134508000000004
+15402,Binary classification,[baseline] Last Class,Elec2,0.8460489578598792,0.8270983738058776,0.0005102157592773438,41.682175
+16308,Binary classification,[baseline] Last Class,Elec2,0.844851904090268,0.8251313243019076,0.0005102157592773438,46.494991
+17214,Binary classification,[baseline] Last Class,Elec2,0.8443618195549875,0.8222177981286084,0.0005102157592773438,51.515798
+18120,Binary classification,[baseline] Last Class,Elec2,0.8450797505381091,0.8227792158595871,0.0005102157592773438,56.800748
+19026,Binary classification,[baseline] Last Class,Elec2,0.8462023653088042,0.8224083515416363,0.0005102157592773438,62.372633
+19932,Binary classification,[baseline] Last Class,Elec2,0.847523957653906,0.8255753888538139,0.0005102157592773438,68.180409
+20838,Binary classification,[baseline] Last Class,Elec2,0.84661899505687,0.8249917862227577,0.0005102157592773438,74.270057
+21744,Binary classification,[baseline] Last Class,Elec2,0.8452835395299637,0.8209495422610177,0.0005102157592773438,80.612623
+22650,Binary classification,[baseline] Last Class,Elec2,0.8444081416398075,0.8188733552631579,0.0005102157592773438,87.17507
+23556,Binary classification,[baseline] Last Class,Elec2,0.8451284228401613,0.8194595664654062,0.0005102157592773438,93.968638
+24462,Binary classification,[baseline] Last Class,Elec2,0.8464903315481788,0.8198781599270878,0.0005102157592773438,100.983267
+25368,Binary classification,[baseline] Last Class,Elec2,0.8462963692986951,0.8199492034172247,0.0005102157592773438,108.278888
+26274,Binary classification,[baseline] Last Class,Elec2,0.8477524454763445,0.8213168944876262,0.0005102157592773438,115.769594
+27180,Binary classification,[baseline] Last Class,Elec2,0.8495529636851982,0.8240457851026293,0.0005102157592773438,123.465792
+28086,Binary classification,[baseline] Last Class,Elec2,0.8509880719245149,0.825107610012955,0.0005102157592773438,131.36678899999998
+28992,Binary classification,[baseline] Last Class,Elec2,0.8521265220240765,0.8258237516759436,0.0005102157592773438,139.55273799999998
+29898,Binary classification,[baseline] Last Class,Elec2,0.8531959728400843,0.8268160833366216,0.0005102157592773438,147.964309
+30804,Binary classification,[baseline] Last Class,Elec2,0.8537480115573158,0.8267107743201139,0.0005102157592773438,156.664426
+31710,Binary classification,[baseline] Last Class,Elec2,0.8530385694913116,0.8259895444361464,0.0005102157592773438,165.606267
+32616,Binary classification,[baseline] Last Class,Elec2,0.8536869538555879,0.8269760696156635,0.0005102157592773438,174.782391
+33522,Binary classification,[baseline] Last Class,Elec2,0.8541511291429253,0.8276032300151628,0.0005102157592773438,184.217189
+34428,Binary classification,[baseline] Last Class,Elec2,0.8549684840386905,0.8286724084685859,0.0005102157592773438,193.875362
+35334,Binary classification,[baseline] Last Class,Elec2,0.8555175048821215,0.8284321962695346,0.0005102157592773438,203.79136499999998
+36240,Binary classification,[baseline] Last Class,Elec2,0.8545213720025387,0.8259146744155329,0.0005102157592773438,213.957306
+37146,Binary classification,[baseline] Last Class,Elec2,0.854354556467896,0.8252696854208386,0.0005102157592773438,224.37720199999998
+38052,Binary classification,[baseline] Last Class,Elec2,0.8545636119944285,0.8247736052181622,0.0005102157592773438,234.998191
+38958,Binary classification,[baseline] Last Class,Elec2,0.8548142824139435,0.8254213223038459,0.0005102157592773438,245.89740899999998
+39864,Binary classification,[baseline] Last Class,Elec2,0.8546521837292728,0.8262981172802495,0.0005102157592773438,257.034489
+40770,Binary classification,[baseline] Last Class,Elec2,0.8540067207927592,0.8267652366261132,0.0005102157592773438,268.379106
+41676,Binary classification,[baseline] Last Class,Elec2,0.8537012597480504,0.8274320002264302,0.0005102157592773438,279.987419
+42582,Binary classification,[baseline] Last Class,Elec2,0.8536201592259458,0.8277177368086459,0.0005102157592773438,291.808183
+43488,Binary classification,[baseline] Last Class,Elec2,0.853473451836181,0.8276626818845675,0.0005102157592773438,303.899029
+44394,Binary classification,[baseline] Last Class,Elec2,0.8533777847858897,0.8271686890948196,0.0005102157592773438,316.239245
+45300,Binary classification,[baseline] Last Class,Elec2,0.8533521711296055,0.8273155007928462,0.0005102157592773438,328.81397599999997
+45312,Binary classification,[baseline] Last Class,Elec2,0.8533027300214076,0.8272294856132872,0.0005102157592773438,341.389555
+25,Binary classification,[baseline] Last Class,Phishing,0.625,0.64,0.0005102157592773438,0.001863
+50,Binary classification,[baseline] Last Class,Phishing,0.6530612244897959,0.6222222222222223,0.0005102157592773438,0.005016
+75,Binary classification,[baseline] Last Class,Phishing,0.5675675675675675,0.5555555555555556,0.0005102157592773438,0.009415
+100,Binary classification,[baseline] Last Class,Phishing,0.5555555555555556,0.5416666666666666,0.0005102157592773438,0.115037
+125,Binary classification,[baseline] Last Class,Phishing,0.5241935483870968,0.5123966942148761,0.0005102157592773438,0.22212700000000002
+150,Binary classification,[baseline] Last Class,Phishing,0.5234899328859061,0.5298013245033113,0.0005102157592773438,0.330326
+175,Binary classification,[baseline] Last Class,Phishing,0.5229885057471264,0.496969696969697,0.0005102157592773438,0.439628
+200,Binary classification,[baseline] Last Class,Phishing,0.507537688442211,0.47872340425531923,0.0005102157592773438,0.550035
+225,Binary classification,[baseline] Last Class,Phishing,0.5,0.45098039215686275,0.0005102157592773438,0.6616070000000001
+250,Binary classification,[baseline] Last Class,Phishing,0.5180722891566265,0.4782608695652174,0.0005102157592773438,0.774476
+275,Binary classification,[baseline] Last Class,Phishing,0.5218978102189781,0.4738955823293172,0.0005102157592773438,0.8884620000000001
+300,Binary classification,[baseline] Last Class,Phishing,0.5217391304347826,0.460377358490566,0.0005102157592773438,1.0035580000000002
+325,Binary classification,[baseline] Last Class,Phishing,0.5216049382716049,0.44839857651245546,0.0005102157592773438,1.151113
+350,Binary classification,[baseline] Last Class,Phishing,0.5329512893982808,0.4511784511784511,0.0005102157592773438,1.299965
+375,Binary classification,[baseline] Last Class,Phishing,0.5267379679144385,0.4380952380952381,0.0005102157592773438,1.4500600000000001
+400,Binary classification,[baseline] Last Class,Phishing,0.5263157894736842,0.43243243243243246,0.0005102157592773438,1.6013830000000002
+425,Binary classification,[baseline] Last Class,Phishing,0.5424528301886793,0.436046511627907,0.0005102157592773438,1.7539290000000003
+450,Binary classification,[baseline] Last Class,Phishing,0.5367483296213809,0.4222222222222222,0.0005102157592773438,1.9077010000000003
+475,Binary classification,[baseline] Last Class,Phishing,0.5358649789029536,0.43298969072164945,0.0005102157592773438,2.0627030000000004
+500,Binary classification,[baseline] Last Class,Phishing,0.5370741482965932,0.44604316546762596,0.0005102157592773438,2.2669650000000003
+525,Binary classification,[baseline] Last Class,Phishing,0.5400763358778626,0.43822843822843827,0.0005102157592773438,2.491531
+550,Binary classification,[baseline] Last Class,Phishing,0.5391621129326047,0.44150110375275936,0.0005102157592773438,2.717762
+575,Binary classification,[baseline] Last Class,Phishing,0.5418118466898955,0.4416135881104034,0.0005102157592773438,2.945135
+600,Binary classification,[baseline] Last Class,Phishing,0.5509181969949917,0.443064182194617,0.0005102157592773438,3.175983
+625,Binary classification,[baseline] Last Class,Phishing,0.5560897435897436,0.43584521384928715,0.0005102157592773438,3.407996
+650,Binary classification,[baseline] Last Class,Phishing,0.551617873651772,0.4393063583815029,0.0005102157592773438,3.641123
+675,Binary classification,[baseline] Last Class,Phishing,0.5459940652818991,0.44363636363636366,0.0005102157592773438,3.8753569999999997
+700,Binary classification,[baseline] Last Class,Phishing,0.5464949928469242,0.4389380530973452,0.0005102157592773438,4.110698999999999
+725,Binary classification,[baseline] Last Class,Phishing,0.5441988950276243,0.44630872483221484,0.0005102157592773438,4.380075
+750,Binary classification,[baseline] Last Class,Phishing,0.5367156208277704,0.44122383252818037,0.0005102157592773438,4.6504829999999995
+775,Binary classification,[baseline] Last Class,Phishing,0.5310077519379846,0.43369734789391573,0.0005102157592773438,4.940408
+800,Binary classification,[baseline] Last Class,Phishing,0.5294117647058824,0.4388059701492537,0.0005102157592773438,5.231503
+825,Binary classification,[baseline] Last Class,Phishing,0.5266990291262136,0.43965517241379315,0.0005102157592773438,5.523716
+850,Binary classification,[baseline] Last Class,Phishing,0.5241460541813898,0.4341736694677871,0.0005102157592773438,5.817038
+875,Binary classification,[baseline] Last Class,Phishing,0.522883295194508,0.4311050477489768,0.0005102157592773438,6.111637
+900,Binary classification,[baseline] Last Class,Phishing,0.5272525027808677,0.4340878828229028,0.0005102157592773438,6.407366
+925,Binary classification,[baseline] Last Class,Phishing,0.5227272727272727,0.43388960205391536,0.0005102157592773438,6.766113
+950,Binary classification,[baseline] Last Class,Phishing,0.5205479452054794,0.43896424167694204,0.0005102157592773438,7.1265789999999996
+975,Binary classification,[baseline] Last Class,Phishing,0.5174537987679672,0.43373493975903615,0.0005102157592773438,7.4884189999999995
+1000,Binary classification,[baseline] Last Class,Phishing,0.5185185185185185,0.4361078546307151,0.0005102157592773438,7.851253
+1025,Binary classification,[baseline] Last Class,Phishing,0.517578125,0.43863636363636366,0.0005102157592773438,8.215067
+1050,Binary classification,[baseline] Last Class,Phishing,0.5138226882745471,0.4370860927152318,0.0005102157592773438,8.579858
+1075,Binary classification,[baseline] Last Class,Phishing,0.5111731843575419,0.43729903536977494,0.0005102157592773438,8.945611
+1100,Binary classification,[baseline] Last Class,Phishing,0.5122838944494995,0.4393305439330544,0.0005102157592773438,9.312327999999999
+1125,Binary classification,[baseline] Last Class,Phishing,0.5124555160142349,0.44534412955465585,0.0005102157592773438,9.680001999999998
+1150,Binary classification,[baseline] Last Class,Phishing,0.5143603133159269,0.44642857142857145,0.0005102157592773438,10.125450999999998
+1175,Binary classification,[baseline] Last Class,Phishing,0.5187393526405452,0.4509232264334305,0.0005102157592773438,10.572147999999999
+1200,Binary classification,[baseline] Last Class,Phishing,0.5187656380316931,0.448901623686724,0.0005102157592773438,11.020091999999998
+1225,Binary classification,[baseline] Last Class,Phishing,0.5171568627450981,0.4471468662301216,0.0005102157592773438,11.469230999999999
+1250,Binary classification,[baseline] Last Class,Phishing,0.5156124899919936,0.4474885844748858,0.0005102157592773438,11.919638999999998
+1903,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,0.335236
+3806,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,1.143886
+5709,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,2.36402
+7612,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,4.028138
+9515,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,6.117771
+11418,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,8.657701
+13321,Binary classification,[baseline] Last Class,SMTP,1.0,0.0,0.00048351287841796875,11.631
+15224,Binary classification,[baseline] Last Class,SMTP,0.9985548183669447,0.0,0.0005102157592773438,15.050370000000001
+17127,Binary classification,[baseline] Last Class,SMTP,0.9984818404764685,0.0,0.0005102157592773438,18.876176
+19030,Binary classification,[baseline] Last Class,SMTP,0.9986336644069578,0.0,0.0005102157592773438,23.061029
+20933,Binary classification,[baseline] Last Class,SMTP,0.9987578826676858,0.0,0.0005102157592773438,27.619004
+22836,Binary classification,[baseline] Last Class,SMTP,0.9988613969783228,0.0,0.0005102157592773438,32.587888
+24739,Binary classification,[baseline] Last Class,SMTP,0.9989489853666425,0.0,0.0005102157592773438,37.966612
+26642,Binary classification,[baseline] Last Class,SMTP,0.9989489884013363,0.0,0.0005102157592773438,43.747015999999995
+28545,Binary classification,[baseline] Last Class,SMTP,0.9990190582959642,0.0,0.0005102157592773438,49.923314999999995
+30448,Binary classification,[baseline] Last Class,SMTP,0.9990803691660919,0.0,0.0005102157592773438,56.476617
+32351,Binary classification,[baseline] Last Class,SMTP,0.9991344667697063,0.0,0.0005102157592773438,63.442318
+34254,Binary classification,[baseline] Last Class,SMTP,0.999182553352991,0.0,0.0005102157592773438,70.796392
+36157,Binary classification,[baseline] Last Class,SMTP,0.9992255780506694,0.0,0.0005102157592773438,78.554987
+38060,Binary classification,[baseline] Last Class,SMTP,0.9992643001655325,0.0,0.0005102157592773438,86.688101
+39963,Binary classification,[baseline] Last Class,SMTP,0.9992993343676493,0.0,0.0005102157592773438,95.30254000000001
+41866,Binary classification,[baseline] Last Class,SMTP,0.9993311835662247,0.0,0.0005102157592773438,104.31052400000002
+43769,Binary classification,[baseline] Last Class,SMTP,0.9993602632059952,0.0,0.0005102157592773438,113.72316700000002
+45672,Binary classification,[baseline] Last Class,SMTP,0.9993869194893915,0.0,0.0005102157592773438,123.54962900000001
+47575,Binary classification,[baseline] Last Class,SMTP,0.9994114432252911,0.0,0.0005102157592773438,133.72455100000002
+49478,Binary classification,[baseline] Last Class,SMTP,0.99943408048184,0.0,0.0005102157592773438,144.361296
+51381,Binary classification,[baseline] Last Class,SMTP,0.9994161152199299,0.0625,0.0005102157592773438,155.342577
+53284,Binary classification,[baseline] Last Class,SMTP,0.9994369686391532,0.0625,0.0005102157592773438,166.71976
+55187,Binary classification,[baseline] Last Class,SMTP,0.9994563838654731,0.0625,0.0005102157592773438,178.568204
+57090,Binary classification,[baseline] Last Class,SMTP,0.9994394717020793,0.36,0.0005102157592773438,190.760423
+58993,Binary classification,[baseline] Last Class,SMTP,0.9994575535665853,0.36,0.0005102157592773438,203.318295
+60896,Binary classification,[baseline] Last Class,SMTP,0.9994745052960013,0.36,0.0005102157592773438,216.324675
+62799,Binary classification,[baseline] Last Class,SMTP,0.9994585814834868,0.37037037037037035,0.0005102157592773438,229.75194900000002
+64702,Binary classification,[baseline] Last Class,SMTP,0.9994745058036197,0.37037037037037035,0.0005102157592773438,243.519605
+66605,Binary classification,[baseline] Last Class,SMTP,0.99948952014894,0.37037037037037035,0.0005102157592773438,257.632512
+68508,Binary classification,[baseline] Last Class,SMTP,0.9994745062548352,0.3793103448275862,0.0005102157592773438,272.164854
+70411,Binary classification,[baseline] Last Class,SMTP,0.9994887089902003,0.3793103448275862,0.0005102157592773438,287.040678
+72314,Binary classification,[baseline] Last Class,SMTP,0.9995021642028404,0.3793103448275862,0.0005102157592773438,302.255295
+74217,Binary classification,[baseline] Last Class,SMTP,0.9995149293952786,0.3793103448275862,0.0005102157592773438,317.85437
+76120,Binary classification,[baseline] Last Class,SMTP,0.99952705631971,0.3793103448275862,0.0005102157592773438,333.81575100000003
+78023,Binary classification,[baseline] Last Class,SMTP,0.99953859167927,0.3793103448275862,0.0005102157592773438,350.111597
+79926,Binary classification,[baseline] Last Class,SMTP,0.999549577729121,0.3793103448275862,0.0005102157592773438,366.757049
+81829,Binary classification,[baseline] Last Class,SMTP,0.9995600527936648,0.3793103448275862,0.0005102157592773438,383.769929
+83732,Binary classification,[baseline] Last Class,SMTP,0.9995700517132244,0.3793103448275862,0.0005102157592773438,401.12604899999997
+85635,Binary classification,[baseline] Last Class,SMTP,0.9995796062311698,0.3793103448275862,0.0005102157592773438,418.85540799999995
+87538,Binary classification,[baseline] Last Class,SMTP,0.999588745330546,0.3793103448275862,0.0005102157592773438,436.927356
+89441,Binary classification,[baseline] Last Class,SMTP,0.9995751341681575,0.36666666666666664,0.0005102157592773438,455.364423
+91344,Binary classification,[baseline] Last Class,SMTP,0.9995839856365567,0.36666666666666664,0.0005102157592773438,474.187698
+93247,Binary classification,[baseline] Last Class,SMTP,0.999592475816657,0.36666666666666664,0.0005102157592773438,493.377496
+95150,Binary classification,[baseline] Last Class,SMTP,0.9996006263859841,0.36666666666666664,0.0005102157592773438,512.867881
+95156,Binary classification,[baseline] Last Class,SMTP,0.9996006515684935,0.36666666666666664,0.0005102157592773438,532.358985
diff --git a/docs/benchmarks/Binary classification/index.md b/docs/benchmarks/Binary classification/index.md
new file mode 100644
index 0000000000..3d8c8e14c0
--- /dev/null
+++ b/docs/benchmarks/Binary classification/index.md	
@@ -0,0 +1,37950 @@
+# Binary classification
+
+
+
+=== "Table"
+
+    | Model                             | Dataset   |   Accuracy |         F1 |   Memory in Mb |   Time in s |
+    |:----------------------------------|:----------|-----------:|-----------:|---------------:|------------:|
+    | ADWIN Bagging                     | Bananas   |   0.625967 | 0.448218   |    0.400658    |    942.73   |
+    | ADWIN Bagging                     | Elec2     |   0.823773 | 0.776587   |    0.598438    |   8970.15   |
+    | ADWIN Bagging                     | Phishing  |   0.893515 | 0.879201   |    1.31008     |    568.218  |
+    | ADWIN Bagging                     | SMTP      |   0.999685 | 0          |    0.164217    |   8006.78   |
+    | ALMA                              | Bananas   |   0.506415 | 0.482595   |    0.0029211   |     68.9731 |
+    | ALMA                              | Elec2     |   0.906427 | 0.889767   |    0.00435829  |    836.498  |
+    | ALMA                              | Phishing  |   0.8256   | 0.810764   |    0.0045805   |     29.7613 |
+    | ALMA                              | SMTP      |   0.764986 | 0.00178548 |    0.00309372  |   1361.61   |
+    | AdaBoost                          | Bananas   |   0.677864 | 0.645041   |    0.453154    |    876.714  |
+    | AdaBoost                          | Elec2     |   0.880581 | 0.858687   |   13.5424      |  10153.7    |
+    | AdaBoost                          | Phishing  |   0.878303 | 0.863555   |    0.873312    |    552.609  |
+    | AdaBoost                          | SMTP      |   0.999443 | 0.404494   |    1.33633     |   6617.5    |
+    | Adaptive Random Forest            | Bananas   |   0.88696  | 0.871707   |   15.3551      |   2603.02   |
+    | Adaptive Random Forest            | Elec2     |   0.876608 | 0.852391   |   22.3949      |  12397.6    |
+    | Adaptive Random Forest            | Phishing  |   0.907926 | 0.896116   |    4.10291     |    743.377  |
+    | Adaptive Random Forest            | SMTP      |   0.999685 | 0          |    0.327095    |  11543.4    |
+    | Aggregated Mondrian Forest        | Bananas   |   0.889413 | 0.874249   |   17.2377      |   2954.75   |
+    | Aggregated Mondrian Forest        | Elec2     |   0.849904 | 0.819731   |  287.315       |  18206.6    |
+    | Aggregated Mondrian Forest        | Phishing  |   0.904724 | 0.892112   |    3.39106     |    807.573  |
+    | Aggregated Mondrian Forest        | SMTP      |   0.999863 | 0.734694   |    0.211749    |   5848.87   |
+    | Bagging                           | Bananas   |   0.634082 | 0.459437   |    0.703124    |   1170.85   |
+    | Bagging                           | Elec2     |   0.840436 | 0.80208    |    2.28896     |  13164.5    |
+    | Bagging                           | Phishing  |   0.893515 | 0.879201   |    1.38826     |    633.136  |
+    | Bagging                           | SMTP      |   0.999685 | 0          |    0.207971    |   8814.84   |
+    | Hoeffding Adaptive Tree           | Bananas   |   0.616531 | 0.42825    |    0.0618467   |    163.516  |
+    | Hoeffding Adaptive Tree           | Elec2     |   0.821258 | 0.787344   |    0.435328    |   2980.69   |
+    | Hoeffding Adaptive Tree           | Phishing  |   0.874299 | 0.856095   |    0.142962    |     77.865  |
+    | Hoeffding Adaptive Tree           | SMTP      |   0.999685 | 0          |    0.0241137   |   2094.95   |
+    | Hoeffding Tree                    | Bananas   |   0.642197 | 0.503405   |    0.0594654   |     93.5302 |
+    | Hoeffding Tree                    | Elec2     |   0.795635 | 0.750834   |    0.938466    |   1485.98   |
+    | Hoeffding Tree                    | Phishing  |   0.879904 | 0.860595   |    0.132719    |     54.2758 |
+    | Hoeffding Tree                    | SMTP      |   0.999685 | 0          |    0.0170441   |   1543.56   |
+    | Leveraging Bagging                | Bananas   |   0.828269 | 0.802689   |    3.23571     |   2747.95   |
+    | Leveraging Bagging                | Elec2     |   0.892653 | 0.871966   |    7.56535     |  18763.3    |
+    | Leveraging Bagging                | Phishing  |   0.894315 | 0.877323   |    4.0114      |   1619.65   |
+    | Leveraging Bagging                | SMTP      |   0.999674 | 0          |    0.164603    |  17549.6    |
+    | Logistic regression               | Bananas   |   0.543208 | 0.197015   |    0.00424099  |     82.0689 |
+    | Logistic regression               | Elec2     |   0.822144 | 0.777086   |    0.005373    |    953.54   |
+    | Logistic regression               | Phishing  |   0.8872   | 0.871233   |    0.00556469  |     29.2066 |
+    | Logistic regression               | SMTP      |   0.999769 | 0.421053   |    0.00438309  |   1531.37   |
+    | Naive Bayes                       | Bananas   |   0.61521  | 0.413912   |    0.0140247   |     97.154  |
+    | Naive Bayes                       | Elec2     |   0.728741 | 0.603785   |    0.0510378   |   1230.66   |
+    | Naive Bayes                       | Phishing  |   0.884708 | 0.871429   |    0.05723     |     38.528  |
+    | Naive Bayes                       | SMTP      |   0.993484 | 0.0490798  |    0.0201406   |   1826.47   |
+    | Stacking                          | Bananas   |   0.876203 | 0.859649   |   19.1946      |   5236.84   |
+    | Stacking                          | Elec2     |   0.885458 | 0.864157   |   40.7547      |  22944.4    |
+    | Stacking                          | Phishing  |   0.895116 | 0.882722   |    8.72124     |   2411.41   |
+    | Stacking                          | SMTP      |   0.999685 | 0          |    4.88868     |  24733.2    |
+    | Streaming Random Patches          | Bananas   |   0.871674 | 0.854265   |   10.5381      |   3551.41   |
+    | Streaming Random Patches          | Elec2     |   0.868884 | 0.843009   |  107.322       |  22969      |
+    | Streaming Random Patches          | Phishing  |   0.913531 | 0.901996   |    6.59559     |   1436.69   |
+    | Streaming Random Patches          | SMTP      |   0.999685 | 0          |    0.17817     |  18142.3    |
+    | Voting                            | Bananas   |   0.872617 | 0.849162   |    4.58403     |   2790.97   |
+    | Voting                            | Elec2     |   0.84368  | 0.797958   |    5.7575      |  13925.5    |
+    | Voting                            | Phishing  |   0.896717 | 0.884512   |    4.8203      |   1436.72   |
+    | Voting                            | SMTP      |   0.999779 | 0.487805   |    4.60205     |  18069.8    |
+    | Vowpal Wabbit logistic regression | Bananas   |   0.551321 | 0          |    0.000646591 |     88.7248 |
+    | Vowpal Wabbit logistic regression | Elec2     |   0.697475 | 0.459592   |    0.000646591 |    937.011  |
+    | Vowpal Wabbit logistic regression | Phishing  |   0.7736   | 0.669778   |    0.000646591 |     27.8334 |
+    | Vowpal Wabbit logistic regression | SMTP      |   0.999695 | 0.121212   |    0.000646591 |   1631.37   |
+    | [baseline] Last Class             | Bananas   |   0.50953  | 0.452957   |    0.000510216 |     30.809  |
+    | [baseline] Last Class             | Elec2     |   0.853303 | 0.827229   |    0.000510216 |    341.39   |
+    | [baseline] Last Class             | Phishing  |   0.515612 | 0.447489   |    0.000510216 |     11.9196 |
+    | [baseline] Last Class             | SMTP      |   0.999601 | 0.366667   |    0.000510216 |    532.359  |
+    | k-Nearest Neighbors               | Bananas   |   0.885073 | 0.870838   |    4.50996     |   2974.33   |
+    | k-Nearest Neighbors               | Elec2     |   0.853148 | 0.823642   |    4.76604     |  13503.4    |
+    | k-Nearest Neighbors               | Phishing  |   0.881505 | 0.867145   |    4.59643     |   1552.65   |
+    | k-Nearest Neighbors               | SMTP      |   0.999821 | 0.666667   |    4.51822     |  17961.1    |
+    | sklearn SGDClassifier             | Bananas   |   0.546415 | 0.205026   |    0.00557804  |    621.426  |
+    | sklearn SGDClassifier             | Elec2     |   0.819099 | 0.772892   |    0.00680161  |   4291.77   |
+    | sklearn SGDClassifier             | Phishing  |   0.8896   | 0.876122   |    0.00701618  |    167.984  |
+    | sklearn SGDClassifier             | SMTP      |   0.999706 | 0.363636   |    0.00574303  |   7118.18   |
+
+=== "Chart"
+
+    *Try reloading the page if something is buggy*
+
+    ```vegalite
+    {
+      "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
+      "data": {
+        "values": [
+          {
+            "step": 106,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.490566037735849,
+            "F1": 0.3414634146341463,
+            "Memory in Mb": 0.0041875839233398,
+            "Time in s": 0.00989
+          },
+          {
+            "step": 212,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5141509433962265,
+            "F1": 0.3832335329341317,
+            "Memory in Mb": 0.0041875839233398,
+            "Time in s": 0.123413
+          },
+          {
+            "step": 318,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5220125786163522,
+            "F1": 0.4242424242424242,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 0.315017
+          },
+          {
+            "step": 424,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5165094339622641,
+            "F1": 0.4023323615160349,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 0.5849610000000001
+          },
+          {
+            "step": 530,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5320754716981132,
+            "F1": 0.3641025641025641,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 0.937213
+          },
+          {
+            "step": 636,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5377358490566038,
+            "F1": 0.3287671232876712,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 1.342505
+          },
+          {
+            "step": 742,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5525606469002695,
+            "F1": 0.3054393305439331,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 1.895068
+          },
+          {
+            "step": 848,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5530660377358491,
+            "F1": 0.2808349146110057,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 2.518365
+          },
+          {
+            "step": 954,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5555555555555556,
+            "F1": 0.2587412587412587,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 3.1930270000000003
+          },
+          {
+            "step": 1060,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5622641509433962,
+            "F1": 0.2418300653594771,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 3.938137
+          },
+          {
+            "step": 1166,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5608919382504288,
+            "F1": 0.2242424242424242,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 4.7351090000000005
+          },
+          {
+            "step": 1272,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5613207547169812,
+            "F1": 0.2206703910614525,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 5.600857
+          },
+          {
+            "step": 1378,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5645863570391872,
+            "F1": 0.20844327176781,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 6.476079
+          },
+          {
+            "step": 1484,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5646900269541779,
+            "F1": 0.1965174129353233,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 7.428853
+          },
+          {
+            "step": 1590,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5647798742138365,
+            "F1": 0.1858823529411764,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 8.473991
+          },
+          {
+            "step": 1696,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5660377358490566,
+            "F1": 0.1785714285714285,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 9.59319
+          },
+          {
+            "step": 1802,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.562708102108768,
+            "F1": 0.1705263157894736,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 10.745503
+          },
+          {
+            "step": 1908,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5587002096436059,
+            "F1": 0.1679841897233201,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 11.962335
+          },
+          {
+            "step": 2014,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5516385302879842,
+            "F1": 0.1662049861495844,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 13.252336
+          },
+          {
+            "step": 2120,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5495283018867925,
+            "F1": 0.1688424717145344,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 14.603624
+          },
+          {
+            "step": 2226,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5485175202156334,
+            "F1": 0.1809290953545232,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 15.981958
+          },
+          {
+            "step": 2332,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5484562607204116,
+            "F1": 0.1967963386727688,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 17.395643
+          },
+          {
+            "step": 2438,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5471698113207547,
+            "F1": 0.1999999999999999,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 18.850781
+          },
+          {
+            "step": 2544,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5479559748427673,
+            "F1": 0.2166212534059945,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 20.422045
+          },
+          {
+            "step": 2650,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5452830188679245,
+            "F1": 0.2260757867694284,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 22.049363
+          },
+          {
+            "step": 2756,
+            "track": "Binary classification",
+            "model": "Logistic regression",
+            "dataset": "Bananas",
+            "Accuracy": 0.5395500725689405,
+            "F1": 0.2285714285714285,
+            "Memory in Mb": 0.0042409896850585,
+            "Time in s": 23.763248
+          },
+          {
+            "step": 2862,
+            "track": "Binary classification",
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+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9994745052960012,
+            "F1": 0.36,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 216.324675
+          },
+          {
+            "step": 62799,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9994585814834868,
+            "F1": 0.3703703703703703,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 229.751949
+          },
+          {
+            "step": 64702,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9994745058036196,
+            "F1": 0.3703703703703703,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 243.519605
+          },
+          {
+            "step": 66605,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.99948952014894,
+            "F1": 0.3703703703703703,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 257.632512
+          },
+          {
+            "step": 68508,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9994745062548352,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 272.164854
+          },
+          {
+            "step": 70411,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9994887089902004,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 287.040678
+          },
+          {
+            "step": 72314,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995021642028404,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 302.255295
+          },
+          {
+            "step": 74217,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995149293952786,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 317.85437
+          },
+          {
+            "step": 76120,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.99952705631971,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 333.81575100000003
+          },
+          {
+            "step": 78023,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.99953859167927,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 350.111597
+          },
+          {
+            "step": 79926,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.999549577729121,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 366.757049
+          },
+          {
+            "step": 81829,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995600527936648,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 383.769929
+          },
+          {
+            "step": 83732,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995700517132244,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 401.126049
+          },
+          {
+            "step": 85635,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995796062311698,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 418.855408
+          },
+          {
+            "step": 87538,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.999588745330546,
+            "F1": 0.3793103448275862,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 436.927356
+          },
+          {
+            "step": 89441,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995751341681576,
+            "F1": 0.3666666666666666,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 455.364423
+          },
+          {
+            "step": 91344,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9995839856365568,
+            "F1": 0.3666666666666666,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 474.187698
+          },
+          {
+            "step": 93247,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.999592475816657,
+            "F1": 0.3666666666666666,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 493.377496
+          },
+          {
+            "step": 95150,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.999600626385984,
+            "F1": 0.3666666666666666,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 512.867881
+          },
+          {
+            "step": 95156,
+            "track": "Binary classification",
+            "model": "[baseline] Last Class",
+            "dataset": "SMTP",
+            "Accuracy": 0.9996006515684936,
+            "F1": 0.3666666666666666,
+            "Memory in Mb": 0.0005102157592773,
+            "Time in s": 532.358985
+          }
+        ]
+      },
+      "params": [
+        {
+          "name": "models",
+          "select": {
+            "type": "point",
+            "fields": [
+              "model"
+            ]
+          },
+          "bind": "legend"
+        },
+        {
+          "name": "Dataset",
+          "value": "Bananas",
+          "bind": {
+            "input": "select",
+            "options": [
+              "Bananas",
+              "Elec2",
+              "Phishing",
+              "SMTP"
+            ]
+          }
+        },
+        {
+          "name": "grid",
+          "select": "interval",
+          "bind": "scales"
+        }
+      ],
+      "transform": [
+        {
+          "filter": {
+            "field": "dataset",
+            "equal": {
+              "expr": "Dataset"
+            }
+          }
+        }
+      ],
+      "repeat": {
+        "row": [
+          "Accuracy",
+          "F1",
+          "Memory in Mb",
+          "Time in s"
+        ]
+      },
+      "spec": {
+        "width": "container",
+        "mark": "line",
+        "encoding": {
+          "x": {
+            "field": "step",
+            "type": "quantitative",
+            "axis": {
+              "titleFontSize": 18,
+              "labelFontSize": 18,
+              "title": "Instance"
+            }
+          },
+          "y": {
+            "field": {
+              "repeat": "row"
+            },
+            "type": "quantitative",
+            "axis": {
+              "titleFontSize": 18,
+              "labelFontSize": 18
+            }
+          },
+          "color": {
+            "field": "model",
+            "type": "ordinal",
+            "scale": {
+              "scheme": "category20b"
+            },
+            "title": "Models",
+            "legend": {
+              "titleFontSize": 18,
+              "labelFontSize": 18,
+              "labelLimit": 500
+            }
+          },
+          "opacity": {
+            "condition": {
+              "param": "models",
+              "value": 1
+            },
+            "value": 0.2
+          }
+        }
+      }
+    }
+    ```
+
+            
+
+## Datasets
+
+???- abstract "Bananas"
+
+    Bananas dataset.
+
+    An artificial dataset where instances belongs to several clusters with a banana shape.
+    There are two attributes that correspond to the x and y axis, respectively.
+
+        Name  Bananas                                                                                                
+        Task  Binary classification                                                                                  
+     Samples  5,300                                                                                                  
+    Features  2                                                                                                      
+      Sparse  False                                                                                                  
+        Path  /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/banana.zip
+
+<span />
+
+???- abstract "Elec2"
+
+    Electricity prices in New South Wales.
+
+    This is a binary classification task, where the goal is to predict if the price of electricity
+    will go up or down.
+
+    This data was collected from the Australian New South Wales Electricity Market. In this market,
+    prices are not fixed and are affected by demand and supply of the market. They are set every
+    five minutes. Electricity transfers to/from the neighboring state of Victoria were done to
+    alleviate fluctuations.
+
+          Name  Elec2                                                      
+          Task  Binary classification                                      
+       Samples  45,312                                                     
+      Features  8                                                          
+        Sparse  False                                                      
+          Path  /Users/mastelini/river_data/Elec2/electricity.csv          
+           URL  https://maxhalford.github.io/files/datasets/electricity.zip
+          Size  2.95 MB                                                    
+    Downloaded  True                                                       
+
+<span />
+
+???- abstract "Phishing"
+
+    Phishing websites.
+
+    This dataset contains features from web pages that are classified as phishing or not.
+
+        Name  Phishing                                                                                                    
+        Task  Binary classification                                                                                       
+     Samples  1,250                                                                                                       
+    Features  9                                                                                                           
+      Sparse  False                                                                                                       
+        Path  /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/phishing.csv.gz
+
+<span />
+
+???- abstract "SMTP"
+
+    SMTP dataset from the KDD 1999 cup.
+
+    The goal is to predict whether or not an SMTP connection is anomalous or not. The dataset only
+    contains 2,211 (0.4%) positive labels.
+
+          Name  SMTP                                                
+          Task  Binary classification                               
+       Samples  95,156                                              
+      Features  3                                                   
+        Sparse  False                                               
+          Path  /Users/mastelini/river_data/SMTP/smtp.csv           
+           URL  https://maxhalford.github.io/files/datasets/smtp.zip
+          Size  5.23 MB                                             
+    Downloaded  True                                                
+
+<span />
+
+## Models
+
+???- example "Logistic regression"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      LogisticRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.005
+          )
+        )
+        loss=Log (
+          weight_pos=1.
+          weight_neg=1.
+        )
+        l2=0.
+        l1=0.
+        intercept_init=0.
+        intercept_lr=Constant (
+          learning_rate=0.01
+        )
+        clip_gradient=1e+12
+        initializer=Zeros ()
+      )
+    )</pre>
+
+<span />
+
+???- example "Aggregated Mondrian Forest"
+
+    <pre>[]</pre>
+
+<span />
+
+???- example "ALMA"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      ALMAClassifier (
+        p=2
+        alpha=0.9
+        B=1.111111
+        C=1.414214
+      )
+    )</pre>
+
+<span />
+
+???- example "sklearn SGDClassifier"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      SKL2RiverClassifier (
+        estimator=SGDClassifier(eta0=0.005, learning_rate='constant', loss='log_loss',
+                    penalty=None)
+        classes=[False, True]
+      )
+    )</pre>
+
+<span />
+
+???- example "Vowpal Wabbit logistic regression"
+
+    <pre>VW2RiverClassifier ()</pre>
+
+<span />
+
+???- example "Naive Bayes"
+
+    <pre>GaussianNB ()</pre>
+
+<span />
+
+???- example "Hoeffding Tree"
+
+    <pre>HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )</pre>
+
+<span />
+
+???- example "Hoeffding Adaptive Tree"
+
+    <pre>HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=True
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=42
+    )</pre>
+
+<span />
+
+???- example "Adaptive Random Forest"
+
+    <pre>[]</pre>
+
+<span />
+
+???- example "Streaming Random Patches"
+
+    <pre>SRPClassifier (
+      model=HoeffdingTreeClassifier (
+        grace_period=50
+        max_depth=inf
+        split_criterion="info_gain"
+        delta=0.01
+        tau=0.05
+        leaf_prediction="nba"
+        nb_threshold=0
+        nominal_attributes=None
+        splitter=GaussianSplitter (
+          n_splits=10
+        )
+        binary_split=False
+        min_branch_fraction=0.01
+        max_share_to_split=0.99
+        max_size=100.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+      )
+      n_models=10
+      subspace_size=0.6
+      training_method="patches"
+      lam=6
+      drift_detector=ADWIN (
+        delta=1e-05
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      warning_detector=ADWIN (
+        delta=0.0001
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      disable_detector="off"
+      disable_weighted_vote=False
+      seed=None
+      metric=Accuracy (
+        cm=ConfusionMatrix (
+          classes=[]
+        )
+      )
+    )</pre>
+
+<span />
+
+???- example "k-Nearest Neighbors"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNClassifier (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        weighted=True
+        cleanup_every=0
+        softmax=False
+      )
+    )</pre>
+
+<span />
+
+???- example "ADWIN Bagging"
+
+    <pre>[HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )]</pre>
+
+<span />
+
+???- example "AdaBoost"
+
+    <pre>[HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )]</pre>
+
+<span />
+
+???- example "Bagging"
+
+    <pre>[HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    )]</pre>
+
+<span />
+
+???- example "Leveraging Bagging"
+
+    <pre>[HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )]</pre>
+
+<span />
+
+???- example "Stacking"
+
+    <pre>[Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      SoftmaxRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=CrossEntropy (
+          class_weight={}
+        )
+        l2=0
+      )
+    ), GaussianNB (), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNClassifier (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        weighted=True
+        cleanup_every=0
+        softmax=False
+      )
+    )]</pre>
+
+<span />
+
+???- example "Voting"
+
+    <pre>VotingClassifier (
+      models=[Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      SoftmaxRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=CrossEntropy (
+          class_weight={}
+        )
+        l2=0
+      )
+    ), GaussianNB (), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNClassifier (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        weighted=True
+        cleanup_every=0
+        softmax=False
+      )
+    )]
+      use_probabilities=True
+    )</pre>
+
+<span />
+
+???- example "[baseline] Last Class"
+
+    <pre>NoChangeClassifier ()</pre>
+
+<span />
+
+## Environment
+
+<pre>Python implementation: CPython
+Python version       : 3.10.13
+IPython version      : 8.16.1
+
+river       : 0.19.0
+numpy       : 1.25.2
+scikit-learn: 1.3.1
+pandas      : 2.1.1
+scipy       : 1.11.3
+
+Compiler    : Clang 14.0.6 
+OS          : Darwin
+Release     : 22.6.0
+Machine     : arm64
+Processor   : arm
+CPU cores   : 8
+Architecture: 64bit
+</pre>
+
diff --git a/docs/benchmarks/Multiclass classification/index.md b/docs/benchmarks/Multiclass classification/index.md
new file mode 100644
index 0000000000..de3b47ecae
--- /dev/null
+++ b/docs/benchmarks/Multiclass classification/index.md	
@@ -0,0 +1,24908 @@
+# Multiclass classification
+
+
+
+=== "Table"
+
+    | Model                      | Dataset       |   Accuracy |   MicroF1 |   MacroF1 |   Memory in Mb |   Time in s |
+    |:---------------------------|:--------------|-----------:|----------:|----------:|---------------:|------------:|
+    | ADWIN Bagging              | ImageSegments |   0.777826 |  0.777826 |  0.765011 |     4.11628    |   3543.55   |
+    | ADWIN Bagging              | Insects       |   0.579465 |  0.579465 |  0.570198 |    15.3074     |  60279.4    |
+    | ADWIN Bagging              | Keystroke     |   0.81656  |  0.81656  |  0.815908 |    37.8558     |  41308      |
+    | AdaBoost                   | ImageSegments |   0.804677 |  0.804677 |  0.79777  |     4.09839    |   3350.88   |
+    | AdaBoost                   | Insects       |   0.563532 |  0.563532 |  0.554622 |    27.943      |  60335.7    |
+    | AdaBoost                   | Keystroke     |   0.834796 |  0.834796 |  0.836062 |   194.794      |  51861.3    |
+    | Adaptive Random Forest     | ImageSegments |   0.818536 |  0.818536 |  0.814535 |     3.06348    |   1574.18   |
+    | Adaptive Random Forest     | Insects       |   0.745378 |  0.745378 |  0.743302 |     0.361794   |  25383.5    |
+    | Adaptive Random Forest     | Keystroke     |   0.969116 |  0.969116 |  0.969111 |     1.63546    |   7363.05   |
+    | Aggregated Mondrian Forest | ImageSegments |   0.901689 |  0.901689 |  0.900381 |    17.0502     |   2997.7    |
+    | Aggregated Mondrian Forest | Insects       |   0.646981 |  0.646981 |  0.644352 |  1365.41       |  76295.7    |
+    | Aggregated Mondrian Forest | Keystroke     |   0.881073 |  0.881073 |  0.879928 |   338.139      |  35528.4    |
+    | Bagging                    | ImageSegments |   0.77696  |  0.77696  |  0.764564 |     4.15507    |   3634.88   |
+    | Bagging                    | Insects       |   0.606392 |  0.606392 |  0.598542 |     3.69162    |  65237      |
+    | Bagging                    | Keystroke     |   0.669739 |  0.669739 |  0.669981 |    50.3449     |  55411.4    |
+    | Hoeffding Adaptive Tree    | ImageSegments |   0.774361 |  0.774361 |  0.763362 |     0.423797   |    457.311  |
+    | Hoeffding Adaptive Tree    | Insects       |   0.613337 |  0.613337 |  0.604219 |     0.143826   |  11292.9    |
+    | Hoeffding Adaptive Tree    | Keystroke     |   0.723124 |  0.723124 |  0.721825 |     0.724475   |   8998.46   |
+    | Hoeffding Tree             | ImageSegments |   0.776094 |  0.776094 |  0.763137 |     0.417154   |    328.067  |
+    | Hoeffding Tree             | Insects       |   0.537306 |  0.537306 |  0.527364 |     2.51923    |   7445.36   |
+    | Hoeffding Tree             | Keystroke     |   0.648218 |  0.648218 |  0.647249 |     5.09445    |   7138.73   |
+    | Leveraging Bagging         | ImageSegments |   0.778259 |  0.778259 |  0.766016 |     4.1005     |   8561.3    |
+    | Leveraging Bagging         | Insects       |   0.695858 |  0.695858 |  0.690508 |    13.831      |  99120.2    |
+    | Leveraging Bagging         | Keystroke     |   0.956616 |  0.956616 |  0.95665  |     7.40999    |  37049.1    |
+    | Naive Bayes                | ImageSegments |   0.731919 |  0.731919 |  0.730419 |     0.390004   |    248.959  |
+    | Naive Bayes                | Insects       |   0.506897 |  0.506897 |  0.493019 |     0.611693   |   4263.77   |
+    | Naive Bayes                | Keystroke     |   0.652532 |  0.652532 |  0.651577 |     4.86901    |   3544.69   |
+    | Stacking                   | ImageSegments |   0.867908 |  0.867908 |  0.865603 |     9.18162    |   5416.88   |
+    | Stacking                   | Insects       |   0.754745 |  0.754745 |  0.752818 |    10.5864     |  72115      |
+    | Stacking                   | Keystroke     |   0.975489 |  0.975489 |  0.975486 |    18.7111     |  42471.8    |
+    | Streaming Random Patches   | ImageSegments |   0.766999 |  0.766999 |  0.764707 |     8.92653    |   6441.81   |
+    | Streaming Random Patches   | Insects       |   0.736163 |  0.736163 |  0.734622 |     9.632      |  90031.6    |
+    | Streaming Random Patches   | Keystroke     |   0.955929 |  0.955929 |  0.95592  |    39.636      |  31009.8    |
+    | Voting                     | ImageSegments |   0.80641  |  0.80641  |  0.798999 |     6.07392    |   3157.94   |
+    | Voting                     | Insects       |   0.648533 |  0.648533 |  0.638    |     9.40652    |  48163.7    |
+    | Voting                     | Keystroke     |   0.779107 |  0.779107 |  0.784136 |    16.3925     |  29779.2    |
+    | [baseline] Last Class      | ImageSegments |   0.148116 |  0.148116 |  0.148116 |     0.00136948 |     31.4159 |
+    | [baseline] Last Class      | Insects       |   0.289761 |  0.289761 |  0.289763 |     0.00138664 |    679.004  |
+    | [baseline] Last Class      | Keystroke     |   0.997549 |  0.997549 |  0.997549 |     0.00504208 |    274.675  |
+    | k-Nearest Neighbors        | ImageSegments |   0.873538 |  0.873538 |  0.872136 |     5.26871    |   2666.29   |
+    | k-Nearest Neighbors        | Insects       |   0.713115 |  0.713115 |  0.711381 |     6.27269    |  40639.9    |
+    | k-Nearest Neighbors        | Keystroke     |   0.910486 |  0.910486 |  0.910328 |     6.32511    |  21326.5    |
+
+=== "Chart"
+
+    *Try reloading the page if something is buggy*
+
+    ```vegalite
+    {
+      "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
+      "data": {
+        "values": [
+          {
+            "step": 46,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.4666666666666667,
+            "MicroF1": 0.4666666666666667,
+            "MacroF1": 0.4009102009102009,
+            "Memory in Mb": 0.3899507522583008,
+            "Time in s": 0.450679
+          },
+          {
+            "step": 92,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5604395604395604,
+            "MicroF1": 0.5604395604395604,
+            "MacroF1": 0.5279334700387331,
+            "Memory in Mb": 0.3899507522583008,
+            "Time in s": 1.152847
+          },
+          {
+            "step": 138,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5474452554744526,
+            "MicroF1": 0.5474452554744526,
+            "MacroF1": 0.5191892873237387,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 2.278305
+          },
+          {
+            "step": 184,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5573770491803278,
+            "MicroF1": 0.5573770491803278,
+            "MacroF1": 0.5225713529323662,
+            "Memory in Mb": 0.3899507522583008,
+            "Time in s": 3.449742
+          },
+          {
+            "step": 230,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5545851528384279,
+            "MicroF1": 0.5545851528384279,
+            "MacroF1": 0.5217226223148511,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 4.939578
+          },
+          {
+            "step": 276,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.56,
+            "MicroF1": 0.56,
+            "MacroF1": 0.5450388711329709,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 6.667081
+          },
+          {
+            "step": 322,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5825545171339563,
+            "MicroF1": 0.5825545171339563,
+            "MacroF1": 0.5566705826058684,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 8.548779999999999
+          },
+          {
+            "step": 368,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5940054495912807,
+            "MicroF1": 0.5940054495912807,
+            "MacroF1": 0.5613773296963412,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 10.607026
+          },
+          {
+            "step": 414,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.5980629539951574,
+            "MicroF1": 0.5980629539951574,
+            "MacroF1": 0.5624927052752284,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 12.811145
+          },
+          {
+            "step": 460,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.599128540305011,
+            "MicroF1": 0.599128540305011,
+            "MacroF1": 0.5669821167583783,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 15.144022
+          },
+          {
+            "step": 506,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6099009900990099,
+            "MicroF1": 0.6099009900990099,
+            "MacroF1": 0.592228619098681,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 17.683543
+          },
+          {
+            "step": 552,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6116152450090744,
+            "MicroF1": 0.6116152450090744,
+            "MacroF1": 0.5983340184133136,
+            "Memory in Mb": 0.3899507522583008,
+            "Time in s": 20.357047
+          },
+          {
+            "step": 598,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6180904522613065,
+            "MicroF1": 0.6180904522613065,
+            "MacroF1": 0.611527101723203,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 23.213992
+          },
+          {
+            "step": 644,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6158631415241057,
+            "MicroF1": 0.6158631415241057,
+            "MacroF1": 0.6113311881078581,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 26.205369
+          },
+          {
+            "step": 690,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6182873730043541,
+            "MicroF1": 0.6182873730043541,
+            "MacroF1": 0.6150189987146761,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 29.350024
+          },
+          {
+            "step": 736,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.617687074829932,
+            "MicroF1": 0.617687074829932,
+            "MacroF1": 0.6157912419016742,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 32.567265
+          },
+          {
+            "step": 782,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6274007682458387,
+            "MicroF1": 0.6274007682458387,
+            "MacroF1": 0.6216325704223051,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 36.027093
+          },
+          {
+            "step": 828,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6324062877871826,
+            "MicroF1": 0.6324062877871826,
+            "MacroF1": 0.6280704917469789,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 39.646129
+          },
+          {
+            "step": 874,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6426116838487973,
+            "MicroF1": 0.6426116838487973,
+            "MacroF1": 0.6349558095046656,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 43.417442
+          },
+          {
+            "step": 920,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6485310119695321,
+            "MicroF1": 0.6485310119695321,
+            "MacroF1": 0.6384515982514894,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 47.360213
+          },
+          {
+            "step": 966,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6507772020725389,
+            "MicroF1": 0.6507772020725389,
+            "MacroF1": 0.6399118827528387,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 51.459671
+          },
+          {
+            "step": 1012,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6508407517309595,
+            "MicroF1": 0.6508407517309595,
+            "MacroF1": 0.6387857120889422,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 55.677121
+          },
+          {
+            "step": 1058,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6537369914853358,
+            "MicroF1": 0.6537369914853358,
+            "MacroF1": 0.6398811322847953,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 60.129657
+          },
+          {
+            "step": 1104,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.658204895738894,
+            "MicroF1": 0.658204895738894,
+            "MacroF1": 0.6463297068165035,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 64.716333
+          },
+          {
+            "step": 1150,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6640557006092254,
+            "MicroF1": 0.6640557006092254,
+            "MacroF1": 0.6508930463144657,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 69.425449
+          },
+          {
+            "step": 1196,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6702928870292887,
+            "MicroF1": 0.6702928870292887,
+            "MacroF1": 0.6599370641329333,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 74.368592
+          },
+          {
+            "step": 1242,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6736502820306205,
+            "MicroF1": 0.6736502820306205,
+            "MacroF1": 0.669511465798708,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 79.42749
+          },
+          {
+            "step": 1288,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6822066822066822,
+            "MicroF1": 0.6822066822066822,
+            "MacroF1": 0.6790074545382362,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 84.676077
+          },
+          {
+            "step": 1334,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6841710427606902,
+            "MicroF1": 0.6841710427606902,
+            "MacroF1": 0.6834974476087327,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 90.04929600000001
+          },
+          {
+            "step": 1380,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6874546773023931,
+            "MicroF1": 0.6874546773023931,
+            "MacroF1": 0.687676692272135,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 95.54439700000002
+          },
+          {
+            "step": 1426,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.6919298245614035,
+            "MicroF1": 0.6919298245614035,
+            "MacroF1": 0.6930786661709784,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 101.25523300000002
+          },
+          {
+            "step": 1472,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.698844323589395,
+            "MicroF1": 0.698844323589395,
+            "MacroF1": 0.6985606658027719,
+            "Memory in Mb": 0.3899774551391601,
+            "Time in s": 107.09626300000002
+          },
+          {
+            "step": 1518,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.7027027027027027,
+            "MicroF1": 0.7027027027027027,
+            "MacroF1": 0.7017787722939461,
+            "Memory in Mb": 0.3900041580200195,
+            "Time in s": 113.17857300000004
+          },
+          {
+            "step": 1564,
+            "track": "Multiclass classification",
+            "model": "Naive Bayes",
+            "dataset": "ImageSegments",
+            "Accuracy": 0.7056941778630839,
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+            "Memory in Mb": 0.0050420761108398,
+            "Time in s": 274.675054
+          }
+        ]
+      },
+      "params": [
+        {
+          "name": "models",
+          "select": {
+            "type": "point",
+            "fields": [
+              "model"
+            ]
+          },
+          "bind": "legend"
+        },
+        {
+          "name": "Dataset",
+          "value": "ImageSegments",
+          "bind": {
+            "input": "select",
+            "options": [
+              "ImageSegments",
+              "Insects",
+              "Keystroke"
+            ]
+          }
+        },
+        {
+          "name": "grid",
+          "select": "interval",
+          "bind": "scales"
+        }
+      ],
+      "transform": [
+        {
+          "filter": {
+            "field": "dataset",
+            "equal": {
+              "expr": "Dataset"
+            }
+          }
+        }
+      ],
+      "repeat": {
+        "row": [
+          "Accuracy",
+          "MicroF1",
+          "MacroF1",
+          "Memory in Mb",
+          "Time in s"
+        ]
+      },
+      "spec": {
+        "width": "container",
+        "mark": "line",
+        "encoding": {
+          "x": {
+            "field": "step",
+            "type": "quantitative",
+            "axis": {
+              "titleFontSize": 18,
+              "labelFontSize": 18,
+              "title": "Instance"
+            }
+          },
+          "y": {
+            "field": {
+              "repeat": "row"
+            },
+            "type": "quantitative",
+            "axis": {
+              "titleFontSize": 18,
+              "labelFontSize": 18
+            }
+          },
+          "color": {
+            "field": "model",
+            "type": "ordinal",
+            "scale": {
+              "scheme": "category20b"
+            },
+            "title": "Models",
+            "legend": {
+              "titleFontSize": 18,
+              "labelFontSize": 18,
+              "labelLimit": 500
+            }
+          },
+          "opacity": {
+            "condition": {
+              "param": "models",
+              "value": 1
+            },
+            "value": 0.2
+          }
+        }
+      }
+    }
+    ```
+
+            
+
+## Datasets
+
+???- abstract "ImageSegments"
+
+    Image segments classification.
+
+    This dataset contains features that describe image segments into 7 classes: brickface, sky,
+    foliage, cement, window, path, and grass.
+
+        Name  ImageSegments                                                                                               
+        Task  Multi-class classification                                                                                  
+     Samples  2,310                                                                                                       
+    Features  18                                                                                                          
+     Classes  7                                                                                                           
+      Sparse  False                                                                                                       
+        Path  /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/segment.csv.zip
+
+<span />
+
+???- abstract "Insects"
+
+    Insects dataset.
+
+    This dataset has different variants, which are:
+
+    - abrupt_balanced
+    - abrupt_imbalanced
+    - gradual_balanced
+    - gradual_imbalanced
+    - incremental-abrupt_balanced
+    - incremental-abrupt_imbalanced
+    - incremental-reoccurring_balanced
+    - incremental-reoccurring_imbalanced
+    - incremental_balanced
+    - incremental_imbalanced
+    - out-of-control
+
+    The number of samples and the difficulty change from one variant to another. The number of
+    classes is always the same (6), except for the last variant (24).
+
+          Name  Insects                                                                                 
+          Task  Multi-class classification                                                              
+       Samples  52,848                                                                                  
+      Features  33                                                                                      
+       Classes  6                                                                                       
+        Sparse  False                                                                                   
+          Path  /Users/mastelini/river_data/Insects/INSECTS-abrupt_balanced_norm.arff                   
+           URL  http://sites.labic.icmc.usp.br/vsouza/repository/creme/INSECTS-abrupt_balanced_norm.arff
+          Size  15.66 MB                                                                                
+    Downloaded  True                                                                                    
+       Variant  abrupt_balanced                                                                         
+
+    Parameters
+    ----------
+        variant
+            Indicates which variant of the dataset to load.
+
+<span />
+
+???- abstract "Keystroke"
+
+    CMU keystroke dataset.
+
+    Users are tasked to type in a password. The task is to determine which user is typing in the
+    password.
+
+    The only difference with the original dataset is that the "sessionIndex" and "rep" attributes
+    have been dropped.
+
+          Name  Keystroke                                                       
+          Task  Multi-class classification                                      
+       Samples  20,400                                                          
+      Features  31                                                              
+       Classes  51                                                              
+        Sparse  False                                                           
+          Path  /Users/mastelini/river_data/Keystroke/DSL-StrongPasswordData.csv
+           URL  http://www.cs.cmu.edu/~keystroke/DSL-StrongPasswordData.csv     
+          Size  4.45 MB                                                         
+    Downloaded  True                                                            
+
+<span />
+
+## Models
+
+???- example "Naive Bayes"
+
+    <pre>GaussianNB ()</pre>
+
+<span />
+
+???- example "Hoeffding Tree"
+
+    <pre>HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )</pre>
+
+<span />
+
+???- example "Hoeffding Adaptive Tree"
+
+    <pre>HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=True
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=42
+    )</pre>
+
+<span />
+
+???- example "Adaptive Random Forest"
+
+    <pre>[]</pre>
+
+<span />
+
+???- example "Aggregated Mondrian Forest"
+
+    <pre>[]</pre>
+
+<span />
+
+???- example "Streaming Random Patches"
+
+    <pre>SRPClassifier (
+      model=HoeffdingTreeClassifier (
+        grace_period=50
+        max_depth=inf
+        split_criterion="info_gain"
+        delta=0.01
+        tau=0.05
+        leaf_prediction="nba"
+        nb_threshold=0
+        nominal_attributes=None
+        splitter=GaussianSplitter (
+          n_splits=10
+        )
+        binary_split=False
+        min_branch_fraction=0.01
+        max_share_to_split=0.99
+        max_size=100.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+      )
+      n_models=10
+      subspace_size=0.6
+      training_method="patches"
+      lam=6
+      drift_detector=ADWIN (
+        delta=1e-05
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      warning_detector=ADWIN (
+        delta=0.0001
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      disable_detector="off"
+      disable_weighted_vote=False
+      seed=None
+      metric=Accuracy (
+        cm=ConfusionMatrix (
+          classes=[]
+        )
+      )
+    )</pre>
+
+<span />
+
+???- example "k-Nearest Neighbors"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNClassifier (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        weighted=True
+        cleanup_every=0
+        softmax=False
+      )
+    )</pre>
+
+<span />
+
+???- example "ADWIN Bagging"
+
+    <pre>[HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )]</pre>
+
+<span />
+
+???- example "AdaBoost"
+
+    <pre>[HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )]</pre>
+
+<span />
+
+???- example "Bagging"
+
+    <pre>[HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    ), HoeffdingAdaptiveTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      bootstrap_sampling=False
+      drift_window_threshold=300
+      drift_detector=ADWIN (
+        delta=0.002
+        clock=32
+        max_buckets=5
+        min_window_length=5
+        grace_period=10
+      )
+      switch_significance=0.05
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+      seed=None
+    )]</pre>
+
+<span />
+
+???- example "Leveraging Bagging"
+
+    <pre>[HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    )]</pre>
+
+<span />
+
+???- example "Stacking"
+
+    <pre>[Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      SoftmaxRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=CrossEntropy (
+          class_weight={}
+        )
+        l2=0
+      )
+    ), GaussianNB (), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNClassifier (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        weighted=True
+        cleanup_every=0
+        softmax=False
+      )
+    )]</pre>
+
+<span />
+
+???- example "Voting"
+
+    <pre>VotingClassifier (
+      models=[Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      SoftmaxRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=CrossEntropy (
+          class_weight={}
+        )
+        l2=0
+      )
+    ), GaussianNB (), HoeffdingTreeClassifier (
+      grace_period=200
+      max_depth=inf
+      split_criterion="info_gain"
+      delta=1e-07
+      tau=0.05
+      leaf_prediction="nba"
+      nb_threshold=0
+      nominal_attributes=None
+      splitter=GaussianSplitter (
+        n_splits=10
+      )
+      binary_split=False
+      min_branch_fraction=0.01
+      max_share_to_split=0.99
+      max_size=100.
+      memory_estimate_period=1000000
+      stop_mem_management=False
+      remove_poor_attrs=False
+      merit_preprune=True
+    ), Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNClassifier (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        weighted=True
+        cleanup_every=0
+        softmax=False
+      )
+    )]
+      use_probabilities=True
+    )</pre>
+
+<span />
+
+???- example "[baseline] Last Class"
+
+    <pre>NoChangeClassifier ()</pre>
+
+<span />
+
+## Environment
+
+<pre>Python implementation: CPython
+Python version       : 3.10.13
+IPython version      : 8.16.1
+
+river       : 0.19.0
+numpy       : 1.25.2
+scikit-learn: 1.3.1
+pandas      : 2.1.1
+scipy       : 1.11.3
+
+Compiler    : Clang 14.0.6 
+OS          : Darwin
+Release     : 22.6.0
+Machine     : arm64
+Processor   : arm
+CPU cores   : 8
+Architecture: 64bit
+</pre>
+
diff --git a/docs/benchmarks/Multiclass classification/multiclass_classification.csv b/docs/benchmarks/Multiclass classification/multiclass_classification.csv
new file mode 100644
index 0000000000..9394fc8dfd
--- /dev/null
+++ b/docs/benchmarks/Multiclass classification/multiclass_classification.csv	
@@ -0,0 +1,2129 @@
+step,track,model,dataset,Accuracy,MicroF1,MacroF1,Memory in Mb,Time in s
+46,Multiclass classification,Naive Bayes,ImageSegments,0.4666666666666667,0.4666666666666667,0.4009102009102009,0.3899507522583008,0.450679
+92,Multiclass classification,Naive Bayes,ImageSegments,0.5604395604395604,0.5604395604395604,0.5279334700387331,0.3899507522583008,1.152847
+138,Multiclass classification,Naive Bayes,ImageSegments,0.5474452554744526,0.5474452554744526,0.5191892873237387,0.38997745513916016,2.278305
+184,Multiclass classification,Naive Bayes,ImageSegments,0.5573770491803278,0.5573770491803278,0.5225713529323662,0.3899507522583008,3.449742
+230,Multiclass classification,Naive Bayes,ImageSegments,0.5545851528384279,0.5545851528384279,0.5217226223148511,0.38997745513916016,4.939578
+276,Multiclass classification,Naive Bayes,ImageSegments,0.56,0.56,0.5450388711329709,0.38997745513916016,6.667081
+322,Multiclass classification,Naive Bayes,ImageSegments,0.5825545171339563,0.5825545171339563,0.5566705826058684,0.39000415802001953,8.548779999999999
+368,Multiclass classification,Naive Bayes,ImageSegments,0.5940054495912807,0.5940054495912807,0.5613773296963412,0.39000415802001953,10.607026
+414,Multiclass classification,Naive Bayes,ImageSegments,0.5980629539951574,0.5980629539951574,0.5624927052752284,0.39000415802001953,12.811145
+460,Multiclass classification,Naive Bayes,ImageSegments,0.599128540305011,0.599128540305011,0.5669821167583783,0.38997745513916016,15.144022
+506,Multiclass classification,Naive Bayes,ImageSegments,0.6099009900990099,0.6099009900990099,0.592228619098681,0.39000415802001953,17.683543
+552,Multiclass classification,Naive Bayes,ImageSegments,0.6116152450090744,0.6116152450090744,0.5983340184133136,0.3899507522583008,20.357047
+598,Multiclass classification,Naive Bayes,ImageSegments,0.6180904522613065,0.6180904522613065,0.611527101723203,0.38997745513916016,23.213992
+644,Multiclass classification,Naive Bayes,ImageSegments,0.6158631415241057,0.6158631415241057,0.6113311881078581,0.38997745513916016,26.205369
+690,Multiclass classification,Naive Bayes,ImageSegments,0.6182873730043541,0.6182873730043541,0.6150189987146761,0.38997745513916016,29.350024
+736,Multiclass classification,Naive Bayes,ImageSegments,0.617687074829932,0.617687074829932,0.6157912419016742,0.38997745513916016,32.567265
+782,Multiclass classification,Naive Bayes,ImageSegments,0.6274007682458387,0.6274007682458387,0.6216325704223051,0.38997745513916016,36.027093
+828,Multiclass classification,Naive Bayes,ImageSegments,0.6324062877871826,0.6324062877871826,0.6280704917469789,0.38997745513916016,39.646129
+874,Multiclass classification,Naive Bayes,ImageSegments,0.6426116838487973,0.6426116838487973,0.6349558095046656,0.38997745513916016,43.417442
+920,Multiclass classification,Naive Bayes,ImageSegments,0.6485310119695321,0.6485310119695321,0.6384515982514894,0.38997745513916016,47.360213
+966,Multiclass classification,Naive Bayes,ImageSegments,0.6507772020725389,0.6507772020725389,0.6399118827528387,0.38997745513916016,51.459671
+1012,Multiclass classification,Naive Bayes,ImageSegments,0.6508407517309595,0.6508407517309595,0.6387857120889422,0.38997745513916016,55.677121
+1058,Multiclass classification,Naive Bayes,ImageSegments,0.6537369914853358,0.6537369914853358,0.6398811322847953,0.38997745513916016,60.129657
+1104,Multiclass classification,Naive Bayes,ImageSegments,0.658204895738894,0.658204895738894,0.6463297068165035,0.38997745513916016,64.716333
+1150,Multiclass classification,Naive Bayes,ImageSegments,0.6640557006092254,0.6640557006092254,0.6508930463144657,0.39000415802001953,69.425449
+1196,Multiclass classification,Naive Bayes,ImageSegments,0.6702928870292887,0.6702928870292887,0.6599370641329333,0.39000415802001953,74.368592
+1242,Multiclass classification,Naive Bayes,ImageSegments,0.6736502820306205,0.6736502820306205,0.669511465798708,0.39000415802001953,79.42749
+1288,Multiclass classification,Naive Bayes,ImageSegments,0.6822066822066822,0.6822066822066822,0.6790074545382362,0.39000415802001953,84.676077
+1334,Multiclass classification,Naive Bayes,ImageSegments,0.6841710427606902,0.6841710427606902,0.6834974476087327,0.39000415802001953,90.04929600000001
+1380,Multiclass classification,Naive Bayes,ImageSegments,0.6874546773023931,0.6874546773023931,0.687676692272135,0.39000415802001953,95.54439700000002
+1426,Multiclass classification,Naive Bayes,ImageSegments,0.6919298245614035,0.6919298245614035,0.6930786661709784,0.39000415802001953,101.25523300000002
+1472,Multiclass classification,Naive Bayes,ImageSegments,0.698844323589395,0.698844323589395,0.6985606658027719,0.38997745513916016,107.09626300000002
+1518,Multiclass classification,Naive Bayes,ImageSegments,0.7027027027027027,0.7027027027027027,0.7017787722939461,0.39000415802001953,113.17857300000003
+1564,Multiclass classification,Naive Bayes,ImageSegments,0.7056941778630839,0.7056941778630839,0.7062915374924865,0.38997745513916016,119.38367200000003
+1610,Multiclass classification,Naive Bayes,ImageSegments,0.7078931013051585,0.7078931013051585,0.7081385387673028,0.38997745513916016,125.72760100000004
+1656,Multiclass classification,Naive Bayes,ImageSegments,0.7093655589123867,0.7093655589123867,0.7109488618373111,0.3899507522583008,132.27559300000004
+1702,Multiclass classification,Naive Bayes,ImageSegments,0.7101704879482658,0.7101704879482658,0.7132092257742534,0.38997745513916016,138.94755600000005
+1748,Multiclass classification,Naive Bayes,ImageSegments,0.7143674871207785,0.7143674871207784,0.7178399485500211,0.3899507522583008,145.68584300000003
+1794,Multiclass classification,Naive Bayes,ImageSegments,0.7172336865588399,0.7172336865588399,0.7191260584555579,0.38997745513916016,152.67811600000005
+1840,Multiclass classification,Naive Bayes,ImageSegments,0.7199564980967917,0.7199564980967917,0.7217017555070446,0.39000415802001953,159.82058900000004
+1886,Multiclass classification,Naive Bayes,ImageSegments,0.7204244031830239,0.7204244031830238,0.7234495525792994,0.39000415802001953,167.13449700000004
+1932,Multiclass classification,Naive Bayes,ImageSegments,0.7219057483169342,0.7219057483169342,0.7238483512148008,0.39000415802001953,174.57489300000003
+1978,Multiclass classification,Naive Bayes,ImageSegments,0.723823975720789,0.723823975720789,0.7251399238639739,0.39000415802001953,182.21825900000005
+2024,Multiclass classification,Naive Bayes,ImageSegments,0.726643598615917,0.726643598615917,0.7268553573885639,0.39000415802001953,189.97396200000006
+2070,Multiclass classification,Naive Bayes,ImageSegments,0.7269212179797003,0.7269212179797003,0.7276782991451582,0.39000415802001953,197.92708900000005
+2116,Multiclass classification,Naive Bayes,ImageSegments,0.7286052009456265,0.7286052009456266,0.7283656039279267,0.39000415802001953,206.04766600000005
+2162,Multiclass classification,Naive Bayes,ImageSegments,0.7306802406293382,0.7306802406293383,0.7303992643507475,0.39000415802001953,214.36632800000004
+2208,Multiclass classification,Naive Bayes,ImageSegments,0.733574988672406,0.733574988672406,0.7322842940126589,0.39000415802001953,222.77231300000003
+2254,Multiclass classification,Naive Bayes,ImageSegments,0.7314691522414558,0.7314691522414558,0.7300322879925133,0.39000415802001953,231.40748800000003
+2300,Multiclass classification,Naive Bayes,ImageSegments,0.7316224445411048,0.7316224445411048,0.7300416811383057,0.39000415802001953,240.14309800000004
+2310,Multiclass classification,Naive Bayes,ImageSegments,0.7319185794716327,0.7319185794716329,0.7304188192194185,0.39000415802001953,248.95897400000004
+1056,Multiclass classification,Naive Bayes,Insects,0.623696682464455,0.623696682464455,0.5870724729616662,0.6116933822631836,4.116407
+2112,Multiclass classification,Naive Bayes,Insects,0.6148744670772146,0.6148744670772146,0.5800776869595596,0.6116933822631836,12.008893
+3168,Multiclass classification,Naive Bayes,Insects,0.6065677297126618,0.6065677297126618,0.5714781230184183,0.6116933822631836,23.636521000000002
+4224,Multiclass classification,Naive Bayes,Insects,0.6043097324177126,0.6043097324177126,0.5697541737710122,0.6116933822631836,38.735534
+5280,Multiclass classification,Naive Bayes,Insects,0.6088274294373934,0.6088274294373934,0.5727560614138387,0.6116933822631836,57.253764000000004
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+1380,Multiclass classification,Hoeffding Tree,ImageSegments,0.7621464829586657,0.7621464829586658,0.7562209880685912,0.4171581268310547,117.79988600000001
+1426,Multiclass classification,Hoeffding Tree,ImageSegments,0.7642105263157895,0.7642105263157895,0.7575332274919562,0.4171581268310547,125.46176800000002
+1472,Multiclass classification,Hoeffding Tree,ImageSegments,0.7688647178789939,0.768864717878994,0.760438686053582,0.4171581268310547,133.360363
+1518,Multiclass classification,Hoeffding Tree,ImageSegments,0.7705998681608438,0.7705998681608438,0.7612069012840872,0.4171581268310547,141.48549400000002
+1564,Multiclass classification,Hoeffding Tree,ImageSegments,0.7709532949456174,0.7709532949456174,0.7622701654854867,0.4171581268310547,149.83563600000002
+1610,Multiclass classification,Hoeffding Tree,ImageSegments,0.7712865133623369,0.771286513362337,0.7617247271717752,0.41718101501464844,158.439217
+1656,Multiclass classification,Hoeffding Tree,ImageSegments,0.7709969788519637,0.7709969788519637,0.7615629120572474,0.41718101501464844,167.22864700000002
+1702,Multiclass classification,Hoeffding Tree,ImageSegments,0.770135214579659,0.770135214579659,0.7627316365695143,0.41718101501464844,176.30742800000002
+1748,Multiclass classification,Hoeffding Tree,ImageSegments,0.7727532913566113,0.7727532913566113,0.7649467707214076,0.41718101501464844,185.609237
+1794,Multiclass classification,Hoeffding Tree,ImageSegments,0.7741215839375348,0.7741215839375348,0.7649332326562149,0.41715431213378906,195.10730800000002
+1840,Multiclass classification,Hoeffding Tree,ImageSegments,0.7754214246873301,0.7754214246873301,0.7664700790631908,0.41715431213378906,204.88888000000003
+1886,Multiclass classification,Hoeffding Tree,ImageSegments,0.7740053050397878,0.7740053050397878,0.7655121135276625,0.41715431213378906,214.87796100000003
+1932,Multiclass classification,Hoeffding Tree,ImageSegments,0.7742102537545313,0.7742102537545313,0.7648034036287765,0.41715431213378906,225.10774000000004
+1978,Multiclass classification,Hoeffding Tree,ImageSegments,0.7754172989377845,0.7754172989377845,0.7656013068970459,0.41715431213378906,235.56491900000003
+2024,Multiclass classification,Hoeffding Tree,ImageSegments,0.7770637666831438,0.7770637666831438,0.7660878232247856,0.41715431213378906,246.31694000000005
+2070,Multiclass classification,Hoeffding Tree,ImageSegments,0.7762203963267279,0.7762203963267279,0.7654829214385931,0.41715431213378906,257.28426500000006
+2116,Multiclass classification,Hoeffding Tree,ImageSegments,0.7768321513002364,0.7768321513002364,0.7653071619305024,0.41715431213378906,268.5154150000001
+2162,Multiclass classification,Hoeffding Tree,ImageSegments,0.7778806108283203,0.7778806108283203,0.7659351904174982,0.41715431213378906,279.94414300000005
+2208,Multiclass classification,Hoeffding Tree,ImageSegments,0.7797915722700498,0.7797915722700498,0.7668192864082087,0.41715431213378906,291.65328600000004
+2254,Multiclass classification,Hoeffding Tree,ImageSegments,0.7767421216156236,0.7767421216156236,0.7637794374955548,0.41715431213378906,303.618395
+2300,Multiclass classification,Hoeffding Tree,ImageSegments,0.7759895606785558,0.7759895606785558,0.763026662835187,0.41715431213378906,315.80512400000003
+2310,Multiclass classification,Hoeffding Tree,ImageSegments,0.776093546990039,0.776093546990039,0.7631372452021826,0.41715431213378906,328.06738900000005
+1056,Multiclass classification,Hoeffding Tree,Insects,0.6218009478672986,0.6218009478672986,0.5852663107194211,0.6579360961914062,7.68277
+2112,Multiclass classification,Hoeffding Tree,Insects,0.6153481762198011,0.6153481762198011,0.5806436317780949,0.6579360961914062,22.565114
+3168,Multiclass classification,Hoeffding Tree,Insects,0.6071992421850332,0.6071992421850332,0.572248584718361,0.6579360961914062,43.997682
+4224,Multiclass classification,Hoeffding Tree,Insects,0.6043097324177126,0.6043097324177126,0.5697573109597247,0.6579360961914062,71.858443
+5280,Multiclass classification,Hoeffding Tree,Insects,0.6088274294373934,0.6088274294373934,0.5727379077413696,0.6579360961914062,105.92483999999999
+6336,Multiclass classification,Hoeffding Tree,Insects,0.6026835043409629,0.6026835043409629,0.568251333238805,0.6579360961914062,146.287253
+7392,Multiclass classification,Hoeffding Tree,Insects,0.600189419564335,0.600189419564335,0.5659762112716077,0.6579360961914062,192.863981
+8448,Multiclass classification,Hoeffding Tree,Insects,0.60258079791642,0.60258079791642,0.5679781484640408,0.6579360961914062,245.806734
+9504,Multiclass classification,Hoeffding Tree,Insects,0.5998105861306956,0.5998105861306956,0.5649597336877693,0.6579360961914062,305.14044
+10560,Multiclass classification,Hoeffding Tree,Insects,0.5998674116867128,0.5998674116867128,0.5650173260529011,0.6579360961914062,370.68089100000003
+11616,Multiclass classification,Hoeffding Tree,Insects,0.5974171330176495,0.5974171330176495,0.5633067089377387,0.6579360961914062,442.33844300000004
+12672,Multiclass classification,Hoeffding Tree,Insects,0.6001894088864336,0.6001894088864336,0.5684760329567131,0.6579360961914062,520.121563
+13728,Multiclass classification,Hoeffding Tree,Insects,0.6120783856632913,0.6120783856632913,0.5935956771555828,0.6579360961914062,604.039429
+14784,Multiclass classification,Hoeffding Tree,Insects,0.6024487587093282,0.6024487587093282,0.5842148300149193,0.6579360961914062,694.113241
+15840,Multiclass classification,Hoeffding Tree,Insects,0.5677757434181451,0.5677757434181451,0.5509250187877572,0.6579360961914062,790.19156
+16896,Multiclass classification,Hoeffding Tree,Insects,0.5419354838709678,0.5419354838709678,0.5257359157219258,0.6579360961914062,892.361186
+17952,Multiclass classification,Hoeffding Tree,Insects,0.5233691716338923,0.5233691716338923,0.5068581838352059,0.6579360961914062,1000.4717479999999
+19008,Multiclass classification,Hoeffding Tree,Insects,0.5121271110643447,0.5121271110643447,0.49292899065094153,0.6579360961914062,1114.494528
+20064,Multiclass classification,Hoeffding Tree,Insects,0.5120370831879579,0.5120370831879579,0.4920970323041603,1.3099584579467773,1234.2056499999999
+21120,Multiclass classification,Hoeffding Tree,Insects,0.5173066906577016,0.5173066906577016,0.4973447169836249,1.310713768005371,1358.925583
+22176,Multiclass classification,Hoeffding Tree,Insects,0.5229312288613304,0.5229312288613304,0.5026343687424488,1.310713768005371,1488.370808
+23232,Multiclass classification,Hoeffding Tree,Insects,0.5301536739701261,0.5301536739701261,0.5095132087733324,1.310713768005371,1622.41448
+24288,Multiclass classification,Hoeffding Tree,Insects,0.5351422571746202,0.5351422571746202,0.5135975374357353,1.310713768005371,1760.8970379999998
+25344,Multiclass classification,Hoeffding Tree,Insects,0.5403069881229531,0.5403069881229531,0.5180803411538233,1.310713768005371,1903.5911449999999
+26400,Multiclass classification,Hoeffding Tree,Insects,0.5441493995984696,0.5441493995984696,0.5209012984387186,1.310713768005371,2050.469487
+27456,Multiclass classification,Hoeffding Tree,Insects,0.5475869604807867,0.5475869604807867,0.5230407124785976,1.310713768005371,2201.55681
+28512,Multiclass classification,Hoeffding Tree,Insects,0.5442460804601733,0.5442460804601733,0.5199893698637053,1.310713768005371,2356.711105
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+30624,Multiclass classification,Hoeffding Tree,Insects,0.5449825294713124,0.5449825294713124,0.5260472440529832,1.310713768005371,2681.5460789999997
+31680,Multiclass classification,Hoeffding Tree,Insects,0.5469238296663405,0.5469238296663405,0.5300194392617626,1.310713768005371,2851.622305
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+33792,Multiclass classification,Hoeffding Tree,Insects,0.5448196265277737,0.5448196265277737,0.5298516474077153,1.310713768005371,3207.119826
+34848,Multiclass classification,Hoeffding Tree,Insects,0.539357763939507,0.539357763939507,0.5246413689313029,1.310713768005371,3392.4010240000002
+35904,Multiclass classification,Hoeffding Tree,Insects,0.5352756037099964,0.5352756037099964,0.5204658240271913,1.310713768005371,3582.6817720000004
+36960,Multiclass classification,Hoeffding Tree,Insects,0.5307232338537298,0.5307232338537298,0.5158458403074864,1.310713768005371,3778.3092850000003
+38016,Multiclass classification,Hoeffding Tree,Insects,0.5287912666052874,0.5287912666052874,0.5138605376143625,1.8479537963867188,3978.8224330000003
+39072,Multiclass classification,Hoeffding Tree,Insects,0.5245322617798367,0.5245322617798367,0.5100329616180462,1.9625730514526367,4184.1075280000005
+40128,Multiclass classification,Hoeffding Tree,Insects,0.5244847608841927,0.5244847608841927,0.5114466799524962,1.9625730514526367,4393.646320000001
+41184,Multiclass classification,Hoeffding Tree,Insects,0.5269650098341548,0.5269650098341548,0.5145630920489553,1.9625730514526367,4606.675677000001
+42240,Multiclass classification,Hoeffding Tree,Insects,0.5290608205686688,0.5290608205686688,0.5171452370879218,1.9625730514526367,4823.052294000001
+43296,Multiclass classification,Hoeffding Tree,Insects,0.5316318281556762,0.5316318281556762,0.5200714653059241,1.9625730514526367,5042.794587000001
+44352,Multiclass classification,Hoeffding Tree,Insects,0.5332912448422809,0.5332912448422809,0.521951703681177,1.9633283615112305,5266.308108000001
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+46464,Multiclass classification,Hoeffding Tree,Insects,0.5374168693368917,0.5374168693368917,0.5257977177437826,1.9633283615112305,5724.562244000002
+47520,Multiclass classification,Hoeffding Tree,Insects,0.5359540394368568,0.5359540394368568,0.5247049329892776,1.9633283615112305,5959.275286000002
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+19992,Multiclass classification,Hoeffding Tree,Keystroke,0.6518433294982742,0.6518433294982742,0.6501496360982542,4.9988250732421875,6781.324361
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+1104,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7461468721668177,0.7461468721668177,0.7413714574148674,0.4238004684448242,106.141078
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+1196,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7506276150627615,0.7506276150627615,0.7460917536510117,0.4234342575073242,123.97312099999999
+1242,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7510072522159549,0.7510072522159549,0.7470578866974922,0.4235563278198242,133.391788
+1288,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.756021756021756,0.7560217560217559,0.7510482446555896,0.4236173629760742,143.113173
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+1426,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7614035087719299,0.7614035087719299,0.7567964121564391,0.4236783981323242,174.36664399999998
+1472,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7654656696125085,0.7654656696125085,0.7591802078998249,0.4236783981323242,185.463757
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+1702,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7677836566725456,0.7677836566725456,0.7627036277641847,0.42376232147216797,245.952092
+1748,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7710360618202633,0.7710360618202633,0.7657334796773966,0.42376232147216797,259.02702999999997
+1794,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7724484104852203,0.7724484104852203,0.7657758298578787,0.4237356185913086,272.39410699999996
+1840,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7737901033170201,0.77379010331702,0.767302943564198,0.4237966537475586,286.06776199999996
+1886,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7724137931034483,0.7724137931034483,0.7666353585191567,0.4237966537475586,300.095471
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+2208,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.777979157227005,0.7779791572270048,0.7670029065892423,0.4237966537475586,407.002801
+2254,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7749667110519307,0.7749667110519308,0.7639707440456852,0.4237966537475586,423.546299
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+2310,Multiclass classification,Hoeffding Adaptive Tree,ImageSegments,0.7743611953226505,0.7743611953226506,0.7633622232911937,0.4237966537475586,457.310729
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+4224,Multiclass classification,Hoeffding Adaptive Tree,Insects,0.603125739995264,0.603125739995264,0.5703574432462961,0.6647005081176758,102.700179
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+8448,Multiclass classification,Hoeffding Adaptive Tree,Insects,0.5989108559251806,0.5989108559251806,0.566418690076869,0.6647615432739258,355.20493799999997
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+13728,Multiclass classification,Hoeffding Adaptive Tree,Insects,0.6097472135207984,0.6097472135207984,0.5927729676671933,0.6648225784301758,874.528885
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+6528,Multiclass classification,Hoeffding Adaptive Tree,Keystroke,0.7585414432357898,0.7585414432357898,0.751418836389106,1.7020492553710938,503.46722600000004
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+42240,Multiclass classification,Adaptive Random Forest,Insects,0.7240464973129098,0.7240464973129098,0.7211005399097123,10.71219539642334,16543.112989
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+44352,Multiclass classification,Adaptive Random Forest,Insects,0.7248765529525828,0.7248765529525828,0.7223628081683402,13.299851417541504,18041.694028
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+52800,Multiclass classification,Adaptive Random Forest,Insects,0.7451466883842497,0.7451466883842497,0.7430487162081567,0.3614501953125,24535.706056000003
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+3264,Multiclass classification,Adaptive Random Forest,Keystroke,0.9672080907140668,0.9672080907140668,0.9546197483047236,4.62060546875,192.073824
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+5712,Multiclass classification,Adaptive Random Forest,Keystroke,0.9690071791279986,0.9690071791279986,0.9686984277929261,4.140267372131348,591.7133210000001
+6120,Multiclass classification,Adaptive Random Forest,Keystroke,0.9671514953423762,0.9671514953423762,0.9635575047511442,5.121949195861816,681.1937680000001
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+6936,Multiclass classification,Adaptive Random Forest,Keystroke,0.9685652487382841,0.9685652487382841,0.9688652926813892,2.7864933013916016,879.0640510000001
+7344,Multiclass classification,Adaptive Random Forest,Keystroke,0.9686776521857552,0.9686776521857552,0.9682274153773371,3.314570426940918,987.0629210000001
+7752,Multiclass classification,Adaptive Random Forest,Keystroke,0.9682621597213262,0.9682621597213262,0.9674704101631952,4.690197944641113,1101.141854
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+9792,Multiclass classification,Adaptive Random Forest,Keystroke,0.9686446736799101,0.9686446736799101,0.9687197530276813,5.552419662475586,1766.078849
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+10608,Multiclass classification,Adaptive Random Forest,Keystroke,0.9673800320543038,0.9673800320543038,0.9668238422002586,3.239151954650879,2074.190769
+11016,Multiclass classification,Adaptive Random Forest,Keystroke,0.9676804357694053,0.9676804357694053,0.9678040910458205,4.023995399475098,2235.420867
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+11832,Multiclass classification,Adaptive Random Forest,Keystroke,0.9677119432000676,0.9677119432000676,0.9677086079179034,5.258674621582031,2574.8706989999996
+12240,Multiclass classification,Adaptive Random Forest,Keystroke,0.9687065936759539,0.9687065936759539,0.9690716756618885,6.001680374145508,2753.3671299999996
+12648,Multiclass classification,Adaptive Random Forest,Keystroke,0.9688463667272871,0.9688463667272871,0.9689334511448673,5.217698097229004,2937.7699639999996
+13056,Multiclass classification,Adaptive Random Forest,Keystroke,0.9687476062811183,0.9687476062811183,0.968764477893114,5.266051292419434,3127.8024029999997
+13464,Multiclass classification,Adaptive Random Forest,Keystroke,0.9687291094109782,0.9687291094109782,0.9687736841624996,6.279603958129883,3323.370395
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+15096,Multiclass classification,Adaptive Random Forest,Keystroke,0.9692613448161643,0.9692613448161643,0.9694122553904638,2.7789316177368164,4151.996270000001
+15504,Multiclass classification,Adaptive Random Forest,Keystroke,0.9694897761723538,0.9694897761723538,0.969571649124791,3.946505546569824,4370.227344000001
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+16728,Multiclass classification,Adaptive Random Forest,Keystroke,0.9692114545345848,0.9692114545345848,0.9692084456743588,1.764338493347168,5057.2303470000015
+17136,Multiclass classification,Adaptive Random Forest,Keystroke,0.9696527575138605,0.9696527575138605,0.9697329621491685,1.7167367935180664,5295.013901000001
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+9504,Multiclass classification,Aggregated Mondrian Forest,Insects,0.7105124697463959,0.7105124697463959,0.6284709935917355,229.19151210784912,2381.431795
+10560,Multiclass classification,Aggregated Mondrian Forest,Insects,0.7140827729898664,0.7140827729898664,0.6302854833117341,253.17632389068604,2925.98814
+11616,Multiclass classification,Aggregated Mondrian Forest,Insects,0.71562634524322,0.7156263452432199,0.6305326785921538,277.4567346572876,3530.8520359999998
+12672,Multiclass classification,Aggregated Mondrian Forest,Insects,0.7145450240707126,0.7145450240707125,0.6284185449457835,301.7114896774292,4201.052974
+13728,Multiclass classification,Aggregated Mondrian Forest,Insects,0.7057623661397247,0.7057623661397247,0.6885364031919957,327.2237205505371,4936.820951
+14784,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6967462625989312,0.6967462625989312,0.69194472505998,352.6018476486206,5738.465999
+15840,Multiclass classification,Aggregated Mondrian Forest,Insects,0.676684134099375,0.676684134099375,0.673854549025314,384.9730758666992,6613.285946
+16896,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6698431488606097,0.6698431488606097,0.668750254945471,415.2214603424072,7559.921071
+17952,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6646983454960727,0.6646983454960727,0.6646134205077884,444.32067584991455,8589.520858
+19008,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6620192560635555,0.6620192560635555,0.6605985532750915,472.75781440734863,9705.665905
+20064,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6597717190848826,0.6597717190848826,0.6570293922418718,499.48760890960693,10901.076562
+21120,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6539608882996354,0.6539608882996354,0.6496192149174075,528.8777961730957,12166.701144
+22176,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6547463359639233,0.6547463359639233,0.6484047117859243,557.1920728683472,13501.384366
+23232,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6583444535319185,0.6583444535319185,0.6499882024630633,584.0554361343384,14901.095396
+24288,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6611767612302878,0.6611767612302878,0.6506059068013808,610.3706150054932,16366.700533000001
+25344,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6659827171210986,0.6659827171210986,0.6532433614752314,635.6853046417236,17901.739193
+26400,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6702526610856472,0.6702526610856472,0.6554263220708306,660.4025926589966,19504.786084
+27456,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6745947914769623,0.6745947914769623,0.6575507550972549,684.36501121521,21172.086014
+28512,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6705482094630143,0.6705482094630143,0.6539581966383304,712.6770572662354,22902.746936
+29568,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6644231744850678,0.6644231744850678,0.6512239029866641,743.5559530258179,24691.477434
+30624,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6622799856317148,0.6622799856317148,0.6527566844616065,772.5478630065918,26538.585641
+31680,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6621736797247388,0.6621736797247388,0.6557760097374935,800.5439138412476,28440.416189000003
+32736,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6623797159004124,0.6623797159004124,0.6584479912704261,827.4998264312744,30418.714512000002
+33792,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6575123553608949,0.6575123553608949,0.6541419435809196,857.7161102294922,32439.386127
+34848,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6519069073377909,0.6519069073377909,0.6481893367707658,888.8327789306641,34499.720344
+35904,Multiclass classification,Aggregated Mondrian Forest,Insects,0.647550343982397,0.647550343982397,0.643407015045196,919.6311988830566,36599.09766
+36960,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6444438431775752,0.6444438431775752,0.6400224052225335,949.7819452285767,38735.650911
+38016,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6425358411153492,0.6425358411153492,0.6377821595167165,979.4456567764282,40896.763764999996
+39072,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6414476209976709,0.6414476209976709,0.6370415360917451,1009.0255756378174,43085.847267
+40128,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6409898572033793,0.6409898572033793,0.636858231937463,1037.841980934143,45303.144751
+41184,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6414782798727631,0.6414782798727631,0.637272014233453,1065.1163549423218,47540.369251
+42240,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6428419233409882,0.6428419233409882,0.6385110475108609,1091.8334274291992,49803.522006
+43296,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6441159487238711,0.6441159487238711,0.6396283228479406,1118.1560363769531,52086.93226
+44352,Multiclass classification,Aggregated Mondrian Forest,Insects,0.645058735992424,0.645058735992424,0.6403851797193834,1144.4119939804077,54391.61903
+45408,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6469266853128373,0.6469266853128373,0.6418265850265934,1169.9601306915283,56719.958571
+46464,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6487742935238792,0.6487742935238792,0.643191402092947,1194.6403436660767,59073.094705
+47520,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6459521454576065,0.6459521454576065,0.6406800374556137,1224.6073780059814,61451.967815
+48576,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6443643849716932,0.6443643849716932,0.6398250343320808,1254.4350862503052,63857.884093
+49632,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6446172754931394,0.6446172754931394,0.6406945505071863,1282.3891849517822,66293.298766
+50688,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6461222798745241,0.6461222798745241,0.6426238276925219,1309.4736614227295,68755.018108
+51744,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6489186943161394,0.6489186943161394,0.6457243405011626,1334.444143295288,71244.151045
+52800,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6470577094263149,0.6470577094263149,0.6443966707674731,1363.999231338501,73759.934152
+52848,Multiclass classification,Aggregated Mondrian Forest,Insects,0.6469809071470471,0.6469809071470471,0.6443518314696601,1365.409776687622,76295.692169
+408,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9901719901719902,0.9901719901719902,0.8308395677472984,0.12276840209960938,1.485322
+816,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9914110429447853,0.9914110429447853,0.960934413925625,0.41584110260009766,6.729082
+1224,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9893704006541292,0.9893704006541292,0.9580466011674303,1.2467107772827148,20.148490000000002
+1632,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9889638258736971,0.9889638258736971,0.9786672150923964,2.28104305267334,50.264957
+2040,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.988719960765081,0.988719960765081,0.9803510904896324,3.352717399597168,91.64343099999999
+2448,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9885574172456069,0.9885574172456069,0.9830468792370581,4.983606338500977,148.278076
+2856,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9852889667250437,0.9852889667250437,0.9737767108051043,6.963967323303223,227.073424
+3264,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9825314128102973,0.9825314128102973,0.9734338986941852,9.8344087600708,324.702985
+3672,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9822936529555979,0.9822936529555979,0.9788760747631073,12.7888765335083,446.35643500000003
+4080,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9806325079676391,0.9806325079676391,0.9749453255203757,16.445659637451172,594.71846
+4488,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9801649208825496,0.9801649208825496,0.9779116862524243,20.943636894226074,768.8230350000001
+4896,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9801838610827375,0.9801838610827375,0.978782474664832,24.856953620910645,967.6114420000001
+5304,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9768055817461814,0.9768055817461814,0.9702080932270808,28.10527801513672,1191.0213970000002
+5712,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9746104009805638,0.9746104009805638,0.9718234131704067,32.14579772949219,1440.171835
+6120,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9697663016832816,0.9697663016832816,0.9621279568251032,36.40912055969238,1717.813161
+6528,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9656810173127011,0.9656810173127011,0.9634765255010708,42.20043754577637,2023.330442
+6936,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9653929343907715,0.9653929343907715,0.9646253117338193,46.972042083740234,2355.811343
+7344,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9635026555903582,0.9635026555903582,0.9611034281810401,50.8284969329834,2716.693574
+7752,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9610372855115469,0.9610372855115469,0.9585597537512924,55.062747955322266,3108.019641
+8160,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9593087388160314,0.9593087388160314,0.9577319445930262,59.75967216491699,3529.9614579999998
+8568,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9598459203922026,0.9598459203922026,0.9601713780248281,65.88526916503906,3981.5521329999997
+8976,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.959108635097493,0.959108635097493,0.9586518345557712,71.85272026062012,4465.222941
+9384,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9573697111797932,0.9573697111797932,0.9561353164275519,78.18439388275146,4984.801354
+9792,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9555714431620876,0.9555714431620876,0.9546392488298882,85.86389446258545,5537.4752260000005
+10200,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9486224139621532,0.9486224139621532,0.9433099305923253,94.35744285583496,6127.477763000001
+10608,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9431507495050439,0.9431507495050439,0.9403442056943527,104.1574821472168,6756.480909000001
+11016,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9408987743985474,0.9408987743985474,0.9399975161043574,113.0038013458252,7421.284759000001
+11424,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9380197846450145,0.9380197846450145,0.936341059397272,121.46645069122314,8125.715779000001
+11832,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9322965091708224,0.9322965091708224,0.9294143034054053,131.1031150817871,8872.899296000001
+12240,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9326742380913473,0.9326742380913473,0.9327603226303838,137.88959789276123,9652.703167000001
+12648,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.927571756147703,0.927571756147703,0.9249549620362734,145.5888376235962,10475.658214000001
+13056,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9247797778628878,0.9247797778628878,0.9237072084771099,154.53871536254883,11346.213643000001
+13464,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9238654088984625,0.9238654088984625,0.9233692422863465,161.3583574295044,12266.045404
+13872,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9202653017086007,0.9202653017086007,0.9191663953636944,170.12918186187744,13231.481182
+14280,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9163106660130261,0.9163106660130261,0.9150341930556871,179.0350112915039,14245.599713
+14688,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9161162933206237,0.9161162933206237,0.9160540991607554,184.834698677063,15311.95464
+15096,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9145412388208016,0.9145412388208016,0.91429667624259,191.58009719848633,16433.239395
+15504,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9105979487841063,0.9105979487841064,0.9097163708309961,200.08039951324463,17613.909715
+15912,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9068568914587393,0.9068568914587393,0.9060681758481206,210.5000762939453,18848.20155
+16320,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9031190636681169,0.9031190636681169,0.9023660107991418,221.55222129821777,20131.794746000003
+16728,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.9005799007592515,0.9005799007592515,0.9001704241319546,231.28063201904297,21466.799965000002
+17136,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8989203384884739,0.8989203384884739,0.8987537815839572,248.11264038085938,22840.808564000003
+17544,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.893746793592886,0.8937467935928861,0.892807745348426,267.53482723236084,24265.711089000004
+17952,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8894212021614395,0.8894212021614395,0.8884694521151855,281.7739496231079,25739.620728000005
+18360,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8911705430579008,0.8911705430579007,0.8908032768807751,288.0978307723999,27256.627666000004
+18768,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8911387009111739,0.8911387009111739,0.8906428613252552,296.05272102355957,28820.747713000004
+19176,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8886049543676662,0.8886049543676662,0.8879368647002966,307.68266773223877,30435.231458000006
+19584,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8895470561201042,0.8895470561201042,0.889061241536932,313.4344787597656,32089.799369000008
+19992,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8862488119653844,0.8862488119653844,0.8855123768505595,324.9442596435547,33786.733744000005
+20400,Multiclass classification,Aggregated Mondrian Forest,Keystroke,0.8810726015981175,0.8810726015981175,0.8799282628097613,338.1390075683594,35528.434162000005
+46,Multiclass classification,Streaming Random Patches,ImageSegments,0.35555555555555557,0.35555555555555557,0.24684873949579833,2.5926971435546875,5.672061
+92,Multiclass classification,Streaming Random Patches,ImageSegments,0.5274725274725275,0.5274725274725275,0.5392220990960486,2.5963096618652344,17.740863
+138,Multiclass classification,Streaming Random Patches,ImageSegments,0.5401459854014599,0.5401459854014599,0.5661177456005042,2.5979232788085938,35.937815
+184,Multiclass classification,Streaming Random Patches,ImageSegments,0.5956284153005464,0.5956284153005464,0.6144104879239446,2.6004638671875,59.975895
+230,Multiclass classification,Streaming Random Patches,ImageSegments,0.6200873362445415,0.6200873362445415,0.6319742698014011,2.6008224487304688,89.681265
+276,Multiclass classification,Streaming Random Patches,ImageSegments,0.6327272727272727,0.6327272727272727,0.6440706793955739,2.601276397705078,125.043898
+322,Multiclass classification,Streaming Random Patches,ImageSegments,0.6573208722741433,0.6573208722741433,0.6535377647060517,2.6028709411621094,166.036362
+368,Multiclass classification,Streaming Random Patches,ImageSegments,0.6784741144414169,0.6784741144414169,0.6717418242612484,2.6031723022460938,212.735146
+414,Multiclass classification,Streaming Random Patches,ImageSegments,0.6900726392251816,0.6900726392251816,0.6823551618652942,2.603717803955078,265.17548899999997
+460,Multiclass classification,Streaming Random Patches,ImageSegments,0.6971677559912854,0.6971677559912854,0.686858403065277,2.6037940979003906,323.486791
+506,Multiclass classification,Streaming Random Patches,ImageSegments,0.699009900990099,0.699009900990099,0.6869845800125663,2.604084014892578,387.600808
+552,Multiclass classification,Streaming Random Patches,ImageSegments,0.6987295825771325,0.6987295825771325,0.6895132041566728,2.6040496826171875,457.32381699999996
+598,Multiclass classification,Streaming Random Patches,ImageSegments,0.7035175879396985,0.7035175879396985,0.6939747146282641,2.6041183471679688,532.682096
+644,Multiclass classification,Streaming Random Patches,ImageSegments,0.6998444790046656,0.6998444790046656,0.6913714585468268,2.6053123474121094,613.490084
+690,Multiclass classification,Streaming Random Patches,ImageSegments,0.7024673439767779,0.7024673439767779,0.6944906634267102,2.6058921813964844,699.880084
+736,Multiclass classification,Streaming Random Patches,ImageSegments,0.7020408163265306,0.7020408163265306,0.69548275919944,2.605987548828125,791.65329
+782,Multiclass classification,Streaming Random Patches,ImageSegments,0.706786171574904,0.706786171574904,0.6991539785967766,2.6064224243164062,888.981823
+828,Multiclass classification,Streaming Random Patches,ImageSegments,0.7085852478839177,0.7085852478839177,0.70309750989463,2.6064682006835938,991.6474969999999
+874,Multiclass classification,Streaming Random Patches,ImageSegments,0.715922107674685,0.7159221076746849,0.7073525059690206,2.6064682006835938,1099.573439
+920,Multiclass classification,Streaming Random Patches,ImageSegments,0.7170837867247007,0.7170837867247007,0.707165908654469,2.6064682006835938,1212.915424
+966,Multiclass classification,Streaming Random Patches,ImageSegments,0.7160621761658031,0.716062176165803,0.7063689525089133,2.6064682006835938,1331.5593390000001
+1012,Multiclass classification,Streaming Random Patches,ImageSegments,0.7151335311572701,0.7151335311572701,0.7047830593764105,2.6064910888671875,1455.3800170000002
+1058,Multiclass classification,Streaming Random Patches,ImageSegments,0.7152317880794702,0.7152317880794702,0.7037726227430311,2.606658935546875,1584.3270810000001
+1104,Multiclass classification,Streaming Random Patches,ImageSegments,0.71441523118767,0.71441523118767,0.7026447500373862,2.6067771911621094,1718.2459470000001
+1150,Multiclass classification,Streaming Random Patches,ImageSegments,0.7162750217580505,0.7162750217580505,0.7030218527348165,2.6067771911621094,1857.0229310000002
+1196,Multiclass classification,Streaming Random Patches,ImageSegments,0.7179916317991631,0.7179916317991631,0.705575475090573,2.379610061645508,2000.273372
+1242,Multiclass classification,Streaming Random Patches,ImageSegments,0.7155519742143432,0.7155519742143431,0.7053749246401603,3.185004234313965,2147.034729
+1288,Multiclass classification,Streaming Random Patches,ImageSegments,0.7156177156177156,0.7156177156177156,0.7041730806550314,3.633350372314453,2296.192092
+1334,Multiclass classification,Streaming Random Patches,ImageSegments,0.7149287321830458,0.7149287321830458,0.7045092702498074,4.368736267089844,2447.850078
+1380,Multiclass classification,Streaming Random Patches,ImageSegments,0.7186366932559826,0.7186366932559827,0.7102131417787841,4.724300384521484,2601.871177
+1426,Multiclass classification,Streaming Random Patches,ImageSegments,0.7256140350877193,0.7256140350877193,0.7174099613082184,4.89253044128418,2758.036552
+1472,Multiclass classification,Streaming Random Patches,ImageSegments,0.7273963290278722,0.7273963290278722,0.7183919320082559,5.412370681762695,2916.512936
+1518,Multiclass classification,Streaming Random Patches,ImageSegments,0.7211601845748187,0.7211601845748187,0.7136134581802791,6.487729072570801,3077.492565
+1564,Multiclass classification,Streaming Random Patches,ImageSegments,0.7172104926423545,0.7172104926423546,0.7129536273040751,6.405126571655273,3241.109
+1610,Multiclass classification,Streaming Random Patches,ImageSegments,0.7209446861404599,0.7209446861404599,0.7163536024764182,6.857941627502441,3407.317179
+1656,Multiclass classification,Streaming Random Patches,ImageSegments,0.7238670694864048,0.7238670694864048,0.7196892738307762,7.034061431884766,3576.2587320000002
+1702,Multiclass classification,Streaming Random Patches,ImageSegments,0.7260435038212816,0.7260435038212816,0.7238533950478148,7.623349189758301,3747.8646120000003
+1748,Multiclass classification,Streaming Random Patches,ImageSegments,0.7309673726388094,0.7309673726388093,0.7286270619416129,8.106144905090332,3922.0639630000005
+1794,Multiclass classification,Streaming Random Patches,ImageSegments,0.7361963190184049,0.7361963190184049,0.7329274067865035,8.185744285583496,4098.8506050000005
+1840,Multiclass classification,Streaming Random Patches,ImageSegments,0.7389885807504079,0.7389885807504077,0.7360694376974826,8.929247856140137,4278.2789060000005
+1886,Multiclass classification,Streaming Random Patches,ImageSegments,0.7411140583554376,0.7411140583554376,0.7396669191579938,9.100563049316406,4460.600751000001
+1932,Multiclass classification,Streaming Random Patches,ImageSegments,0.7431382703262558,0.7431382703262558,0.7411378754700444,9.223885536193848,4645.683986000001
+1978,Multiclass classification,Streaming Random Patches,ImageSegments,0.7465857359635811,0.746585735963581,0.744200926808846,9.401692390441895,4833.458731000001
+2024,Multiclass classification,Streaming Random Patches,ImageSegments,0.7508650519031141,0.7508650519031143,0.7476945996538615,9.481804847717285,5024.230846
+2070,Multiclass classification,Streaming Random Patches,ImageSegments,0.7549540840985983,0.7549540840985983,0.7524477298078486,9.431160926818848,5217.969956000001
+2116,Multiclass classification,Streaming Random Patches,ImageSegments,0.7583924349881797,0.7583924349881797,0.7554386161495508,9.549637794494629,5414.604524000001
+2162,Multiclass classification,Streaming Random Patches,ImageSegments,0.7607589079130033,0.7607589079130033,0.7577216433051415,10.151451110839844,5614.378132000002
+2208,Multiclass classification,Streaming Random Patches,ImageSegments,0.7648391481649298,0.7648391481649298,0.7614528787516565,9.14443588256836,5817.274926000002
+2254,Multiclass classification,Streaming Random Patches,ImageSegments,0.7652019529516201,0.7652019529516201,0.762166830901651,8.801234245300293,6023.198429000002
+2300,Multiclass classification,Streaming Random Patches,ImageSegments,0.7672901261418008,0.7672901261418008,0.7647372124971393,8.857858657836914,6232.074878000002
+2310,Multiclass classification,Streaming Random Patches,ImageSegments,0.7669987007362494,0.7669987007362494,0.7647069285577738,8.926526069641113,6441.814766000002
+1056,Multiclass classification,Streaming Random Patches,Insects,0.6388625592417062,0.6388625592417062,0.6031100134310133,8.730474472045898,177.190345
+2112,Multiclass classification,Streaming Random Patches,Insects,0.659403126480341,0.659403126480341,0.6244477305834598,21.138185501098633,477.66892900000005
+3168,Multiclass classification,Streaming Random Patches,Insects,0.6722450268392801,0.6722450268392801,0.6321534006670183,28.433568000793457,884.814326
+4224,Multiclass classification,Streaming Random Patches,Insects,0.680322045938906,0.680322045938906,0.6340126191391743,39.2259521484375,1406.7405990000002
+5280,Multiclass classification,Streaming Random Patches,Insects,0.6878196628149271,0.6878196628149271,0.6395508722492685,32.51231288909912,2046.4837620000003
+6336,Multiclass classification,Streaming Random Patches,Insects,0.6876085240726125,0.6876085240726125,0.641396967542699,34.576416969299316,2792.1074670000003
+7392,Multiclass classification,Streaming Random Patches,Insects,0.6924638073332431,0.6924638073332431,0.6467777725107727,40.06835174560547,3634.422347
+8448,Multiclass classification,Streaming Random Patches,Insects,0.6949212738250267,0.6949212738250267,0.6476372139610082,43.01965808868408,4571.1184410000005
+9504,Multiclass classification,Streaming Random Patches,Insects,0.6992528675155214,0.6992528675155214,0.6494082466298291,45.71251583099365,5608.992399000001
+10560,Multiclass classification,Streaming Random Patches,Insects,0.7013921772895161,0.7013921772895161,0.6506452100316108,50.310431480407715,6744.395149000001
+11616,Multiclass classification,Streaming Random Patches,Insects,0.7043478260869566,0.7043478260869566,0.6524912605091605,59.279197692871094,7964.619750000001
+12672,Multiclass classification,Streaming Random Patches,Insects,0.7079946334148843,0.7079946334148843,0.6596828376773001,72.61201000213623,9269.589572
+13728,Multiclass classification,Streaming Random Patches,Insects,0.7208421359364756,0.7208421359364756,0.7145906055666686,38.78250694274902,10625.218377000001
+14784,Multiclass classification,Streaming Random Patches,Insects,0.7285395386592708,0.7285395386592708,0.7256542392368915,15.546477317810059,12027.231464
+15840,Multiclass classification,Streaming Random Patches,Insects,0.7206263021655408,0.7206263021655408,0.7196216319492748,14.88278579711914,13491.676191
+16896,Multiclass classification,Streaming Random Patches,Insects,0.7171352471145309,0.7171352471145309,0.7175260611854538,21.28149700164795,15025.812845
+17952,Multiclass classification,Streaming Random Patches,Insects,0.7121051751991533,0.7121051751991533,0.7136617513297842,29.336480140686035,16621.157643
+19008,Multiclass classification,Streaming Random Patches,Insects,0.7205240174672489,0.720524017467249,0.7180961996594418,20.976608276367188,18267.655244999998
+20064,Multiclass classification,Streaming Random Patches,Insects,0.7261625878482779,0.7261625878482779,0.7198561207408494,15.994047164916992,19960.279520999997
+21120,Multiclass classification,Streaming Random Patches,Insects,0.7272598134381363,0.7272598134381363,0.7183389579277755,17.52824878692627,21708.029386999995
+22176,Multiclass classification,Streaming Random Patches,Insects,0.7281623449830891,0.7281623449830891,0.7167723651435352,22.240838050842285,23503.558300999994
+23232,Multiclass classification,Streaming Random Patches,Insects,0.7307477078042272,0.7307477078042272,0.7170791531651185,26.114503860473633,25348.434525999994
+24288,Multiclass classification,Streaming Random Patches,Insects,0.7325318071396221,0.7325318071396222,0.7165563330554671,27.974491119384766,27240.683159999993
+25344,Multiclass classification,Streaming Random Patches,Insects,0.7353904431203883,0.7353904431203884,0.7174524973348954,37.12833023071289,29182.513668999993
+26400,Multiclass classification,Streaming Random Patches,Insects,0.7367703322095533,0.7367703322095533,0.7168965346030137,31.575971603393555,31184.058177999992
+27456,Multiclass classification,Streaming Random Patches,Insects,0.738371881260244,0.738371881260244,0.7164257197178175,35.22733116149902,33213.34443999999
+28512,Multiclass classification,Streaming Random Patches,Insects,0.7366279681526429,0.7366279681526429,0.7161250847684691,17.50509262084961,35271.15690999999
+29568,Multiclass classification,Streaming Random Patches,Insects,0.7354483038522678,0.7354483038522677,0.719616514898752,22.40646266937256,37354.25785299999
+30624,Multiclass classification,Streaming Random Patches,Insects,0.7348724814681775,0.7348724814681775,0.7237598149406717,31.226743698120117,39459.628930999985
+31680,Multiclass classification,Streaming Random Patches,Insects,0.7347769815966413,0.7347769815966413,0.7275990709197302,35.24118995666504,41587.294746999985
+32736,Multiclass classification,Streaming Random Patches,Insects,0.7351458683366427,0.7351458683366427,0.7308983066693725,48.40772724151611,43729.930447999985
+33792,Multiclass classification,Streaming Random Patches,Insects,0.7303423988636027,0.7303423988636027,0.7274356410957497,77.28174114227295,45887.55412199999
+34848,Multiclass classification,Streaming Random Patches,Insects,0.726805750853732,0.726805750853732,0.723911701718825,53.16175174713135,48068.300588999984
+35904,Multiclass classification,Streaming Random Patches,Insects,0.7248976408656658,0.7248976408656659,0.7218080521646734,41.53026580810547,50265.619736999986
+36960,Multiclass classification,Streaming Random Patches,Insects,0.7215833761735978,0.7215833761735979,0.7182506744185386,35.33352756500244,52485.185911999986
+38016,Multiclass classification,Streaming Random Patches,Insects,0.7196369854004998,0.7196369854004999,0.7160236415660819,44.00273513793945,54721.05808499999
+39072,Multiclass classification,Streaming Random Patches,Insects,0.7175142688950884,0.7175142688950884,0.713988650041017,46.12203025817871,56978.30571199999
+40128,Multiclass classification,Streaming Random Patches,Insects,0.7158023276098388,0.7158023276098388,0.7126852582249207,27.841010093688965,59249.54765999999
+41184,Multiclass classification,Streaming Random Patches,Insects,0.7157322196051769,0.715732219605177,0.7129296468122535,21.849401473999023,61534.70422899999
+42240,Multiclass classification,Streaming Random Patches,Insects,0.7156656170837378,0.7156656170837377,0.7131576552849198,28.021278381347656,63833.596648999985
+43296,Multiclass classification,Streaming Random Patches,Insects,0.715925626515764,0.715925626515764,0.7137513847694824,36.50454139709473,66146.66403399999
+44352,Multiclass classification,Streaming Random Patches,Insects,0.7161958016730176,0.7161958016730177,0.7143198962298327,46.888444900512695,68474.34057599999
+45408,Multiclass classification,Streaming Random Patches,Insects,0.7170260092056291,0.7170260092056291,0.7151715877390813,47.08374786376953,70816.527322
+46464,Multiclass classification,Streaming Random Patches,Insects,0.7181843617502098,0.7181843617502098,0.7162864260409335,43.18325901031494,73172.526917
+47520,Multiclass classification,Streaming Random Patches,Insects,0.7179023127591069,0.7179023127591069,0.716246618663062,54.80090522766113,75543.857611
+48576,Multiclass classification,Streaming Random Patches,Insects,0.7211528564076171,0.7211528564076171,0.719707905487922,60.4919376373291,77931.086228
+49632,Multiclass classification,Streaming Random Patches,Insects,0.7250710241582882,0.7250710241582882,0.7236001513027165,35.55128765106201,80332.853368
+50688,Multiclass classification,Streaming Random Patches,Insects,0.7288259316984631,0.7288259316984631,0.7271241427068512,21.017152786254883,82746.274567
+51744,Multiclass classification,Streaming Random Patches,Insects,0.7329107318864387,0.7329107318864386,0.7308784460773333,26.768343925476074,85169.877802
+52800,Multiclass classification,Streaming Random Patches,Insects,0.7359230288452433,0.7359230288452432,0.7343606492383059,9.57052230834961,87600.592492
+52848,Multiclass classification,Streaming Random Patches,Insects,0.7361628853104244,0.7361628853104244,0.7346220154259927,9.63199520111084,90031.55993999999
+408,Multiclass classification,Streaming Random Patches,Keystroke,0.9901719901719902,0.9901719901719902,0.8308395677472984,1.027322769165039,17.348128
+816,Multiclass classification,Streaming Random Patches,Keystroke,0.9877300613496932,0.9877300613496932,0.9320293882508496,2.6651391983032227,54.406226000000004
+1224,Multiclass classification,Streaming Random Patches,Keystroke,0.9828291087489779,0.9828291087489779,0.9464059415055075,5.679329872131348,114.007104
+1632,Multiclass classification,Streaming Random Patches,Keystroke,0.9828326180257511,0.9828326180257511,0.9632097550305241,8.335807800292969,201.582874
+2040,Multiclass classification,Streaming Random Patches,Keystroke,0.9749877390877881,0.9749877390877881,0.9373958892668122,12.631415367126465,318.920922
+2448,Multiclass classification,Streaming Random Patches,Keystroke,0.9701675521046179,0.9701675521046179,0.957381800109682,16.891732215881348,465.74626
+2856,Multiclass classification,Streaming Random Patches,Keystroke,0.9660245183887916,0.9660245183887916,0.9394754450400101,22.937668800354004,641.328845
+3264,Multiclass classification,Streaming Random Patches,Keystroke,0.9616916947594238,0.9616916947594238,0.9454054748805115,29.12161636352539,847.207258
+3672,Multiclass classification,Streaming Random Patches,Keystroke,0.9607736311631708,0.9607736311631708,0.953605417859829,28.669262886047363,1081.626023
+4080,Multiclass classification,Streaming Random Patches,Keystroke,0.9578328021573915,0.9578328021573915,0.9463612240153171,34.20732402801514,1345.493591
+4488,Multiclass classification,Streaming Random Patches,Keystroke,0.9589926454201025,0.9589926454201025,0.9613092683363473,18.652557373046875,1636.499529
+4896,Multiclass classification,Streaming Random Patches,Keystroke,0.9607763023493361,0.9607763023493361,0.9605208703626084,20.81053066253662,1952.783692
+5304,Multiclass classification,Streaming Random Patches,Keystroke,0.9615312087497643,0.9615312087497643,0.9603033149830379,27.91543483734131,2294.145458
+5712,Multiclass classification,Streaming Random Patches,Keystroke,0.9616529504465068,0.9616529504465068,0.9605387671994151,32.60424041748047,2660.691575
+6120,Multiclass classification,Streaming Random Patches,Keystroke,0.9597973525085798,0.9597973525085798,0.9561203427932812,39.11091995239258,3053.1932039999997
+6528,Multiclass classification,Streaming Random Patches,Keystroke,0.9589397885705531,0.9589397885705531,0.9571591040678328,29.255366325378418,3470.643733
+6936,Multiclass classification,Streaming Random Patches,Keystroke,0.959913482335977,0.959913482335977,0.9605956598361813,31.930577278137207,3910.602191
+7344,Multiclass classification,Streaming Random Patches,Keystroke,0.9602342366880022,0.9602342366880022,0.9598619882355601,26.562703132629395,4374.151898
+7752,Multiclass classification,Streaming Random Patches,Keystroke,0.9601341762353245,0.9601341762353245,0.9596510454605859,31.588034629821777,4858.190889
+8160,Multiclass classification,Streaming Random Patches,Keystroke,0.9584507905380562,0.9584507905380562,0.9567204261955369,39.12565612792969,5363.543193
+8568,Multiclass classification,Streaming Random Patches,Keystroke,0.9579782887825377,0.9579782887825377,0.957794146577291,44.816758155822754,5892.06228
+8976,Multiclass classification,Streaming Random Patches,Keystroke,0.9579944289693594,0.9579944289693594,0.9581242571113369,49.5586576461792,6445.036349
+9384,Multiclass classification,Streaming Random Patches,Keystroke,0.9570499840136417,0.9570499840136417,0.9565283447410108,50.185367584228516,7025.065903
+9792,Multiclass classification,Streaming Random Patches,Keystroke,0.9563885200694515,0.9563885200694515,0.9560487952418978,54.40623474121094,7630.795018999999
+10200,Multiclass classification,Streaming Random Patches,Keystroke,0.9532307088930287,0.9532307088930287,0.9512518567217172,66.82855319976807,8267.200675
+10608,Multiclass classification,Streaming Random Patches,Keystroke,0.9519185443574998,0.9519185443574998,0.9512557409849248,41.17615795135498,8934.408603
+11016,Multiclass classification,Streaming Random Patches,Keystroke,0.9528824330458465,0.9528824330458465,0.953398407731189,32.87209510803223,9625.903537
+11424,Multiclass classification,Streaming Random Patches,Keystroke,0.953689923837871,0.953689923837871,0.9540175301991308,28.078542709350586,10339.782646
+11832,Multiclass classification,Streaming Random Patches,Keystroke,0.9542726734849125,0.9542726734849125,0.9545119777330118,20.280012130737305,11070.86282
+12240,Multiclass classification,Streaming Random Patches,Keystroke,0.955470218155078,0.955470218155078,0.9559406438939211,21.54300308227539,11820.445116
+12648,Multiclass classification,Streaming Random Patches,Keystroke,0.9559579346880683,0.9559579346880683,0.9561632451269845,26.89114284515381,12588.394717000001
+13056,Multiclass classification,Streaming Random Patches,Keystroke,0.9558789735733435,0.9558789735733435,0.9559075747932771,21.382742881774902,13375.587705000002
+13464,Multiclass classification,Streaming Random Patches,Keystroke,0.9563247418851668,0.9563247418851668,0.9565051554876024,21.864919662475586,14180.689980000001
+13872,Multiclass classification,Streaming Random Patches,Keystroke,0.9569605652079879,0.9569605652079879,0.9571856017401091,25.72835636138916,15004.794290000002
+14280,Multiclass classification,Streaming Random Patches,Keystroke,0.9566496253239022,0.9566496253239022,0.9566382966080723,21.764866828918457,15848.339318000002
+14688,Multiclass classification,Streaming Random Patches,Keystroke,0.957241097569279,0.9572410975692791,0.957426459656079,25.14582061767578,16708.048820000004
+15096,Multiclass classification,Streaming Random Patches,Keystroke,0.9580655846306724,0.9580655846306724,0.9582773620158959,26.658535957336426,17588.164126000003
+15504,Multiclass classification,Streaming Random Patches,Keystroke,0.9584596529703928,0.9584596529703928,0.9585840009788793,30.767892837524414,18489.703328000003
+15912,Multiclass classification,Streaming Random Patches,Keystroke,0.9580793161963421,0.9580793161963421,0.9580713134265897,27.786094665527344,19412.324967000004
+16320,Multiclass classification,Streaming Random Patches,Keystroke,0.958514614866107,0.958514614866107,0.9586173296332885,25.79348850250244,20355.979039000005
+16728,Multiclass classification,Streaming Random Patches,Keystroke,0.9577330065164106,0.9577330065164106,0.9576699214368118,33.630208015441895,21321.132478000007
+17136,Multiclass classification,Streaming Random Patches,Keystroke,0.9576305806828129,0.9576305806828129,0.9576693803774444,33.920249938964844,22315.653729000005
+17544,Multiclass classification,Streaming Random Patches,Keystroke,0.956506868836573,0.956506868836573,0.9564470129227677,31.505155563354492,23335.132930000003
+17952,Multiclass classification,Streaming Random Patches,Keystroke,0.9563812600969306,0.9563812600969306,0.9564135249623555,19.79563045501709,24372.247222
+18360,Multiclass classification,Streaming Random Patches,Keystroke,0.9569148646440437,0.9569148646440437,0.9569804233582649,23.70892333984375,25428.663478000002
+18768,Multiclass classification,Streaming Random Patches,Keystroke,0.9574252677572335,0.9574252677572335,0.957475477736454,21.893744468688965,26504.246634000003
+19176,Multiclass classification,Streaming Random Patches,Keystroke,0.9568187744458931,0.9568187744458931,0.956806677474395,28.04871368408203,27598.635240000003
+19584,Multiclass classification,Streaming Random Patches,Keystroke,0.9567992646683348,0.9567992646683348,0.9568012672257533,32.11082458496094,28712.463090000005
+19992,Multiclass classification,Streaming Random Patches,Keystroke,0.9565304386974138,0.9565304386974138,0.9565268274864178,40.13526153564453,29849.822929000005
+20400,Multiclass classification,Streaming Random Patches,Keystroke,0.9559292122162851,0.9559292122162851,0.9559196349550496,39.63601016998291,31009.846621000004
+46,Multiclass classification,k-Nearest Neighbors,ImageSegments,0.5111111111111111,0.5111111111111111,0.40938578329882686,0.09116363525390625,0.155273
+92,Multiclass classification,k-Nearest Neighbors,ImageSegments,0.6043956043956044,0.6043956043956044,0.5940974230447915,0.16827392578125,0.72683
+138,Multiclass classification,k-Nearest Neighbors,ImageSegments,0.6715328467153284,0.6715328467153284,0.6806196928151186,0.24543190002441406,1.742293
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+11016,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9106672719019518,0.9106672719019518,0.911227786024665,6.261377334594727,7300.041981000002
+11424,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9103562986956141,0.9103562986956141,0.9101104800687125,6.227293968200684,7769.979179000002
+11832,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9092215366410278,0.9092215366410278,0.9094186121236619,6.287784576416016,8252.975566000001
+12240,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9110221423318898,0.9110221423318898,0.9118339797691071,6.31197452545166,8747.696417000001
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+13056,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9129069322098813,0.9129069322098813,0.913006147591119,6.346117973327637,9774.692327
+13464,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9136150932184506,0.9136150932184506,0.9138210444048112,6.238006591796875,10306.725428000002
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+15504,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9127910726956073,0.9127910726956073,0.9127632118282708,6.222077369689941,13158.500651999999
+15912,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9127019043429074,0.9127019043429074,0.9127365496247325,6.263586044311523,13766.752283999998
+16320,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9113303511244562,0.9113303511244562,0.9110956080213111,6.256609916687012,14388.121761999999
+16728,Multiclass classification,k-Nearest Neighbors,Keystroke,0.910384408441442,0.9103844084414419,0.9103324360258119,6.2080230712890625,15023.088924
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+19992,Multiclass classification,k-Nearest Neighbors,Keystroke,0.9111099994997749,0.9111099994997749,0.910917465793804,6.225028991699219,20571.760391
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+45408,Multiclass classification,ADWIN Bagging,Insects,0.5541436342414165,0.5541436342414165,0.5454957405719211,14.18911075592041,45215.90786900002
+46464,Multiclass classification,ADWIN Bagging,Insects,0.5553020683124207,0.5553020683124207,0.546961663735647,15.156656265258789,47024.86244100002
+47520,Multiclass classification,ADWIN Bagging,Insects,0.5579662871693428,0.5579662871693428,0.5498636684303295,14.218542098999023,48856.78116300002
+48576,Multiclass classification,ADWIN Bagging,Insects,0.5627586206896552,0.5627586206896552,0.5545030394801858,14.845645904541016,50711.770017000024
+49632,Multiclass classification,ADWIN Bagging,Insects,0.5677701436602124,0.5677701436602124,0.5591808574875289,15.233248710632324,52589.43568900003
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+51744,Multiclass classification,ADWIN Bagging,Insects,0.5791894555785324,0.5791894555785324,0.5695807960578061,16.1916446685791,56406.77001200003
+52800,Multiclass classification,ADWIN Bagging,Insects,0.5794427924771303,0.5794427924771303,0.5701512686040561,15.307219505310059,58342.70756100003
+52848,Multiclass classification,ADWIN Bagging,Insects,0.5794652487369197,0.5794652487369197,0.5701984940722999,15.307356834411621,60279.413314000034
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+1224,Multiclass classification,ADWIN Bagging,Keystroke,0.8912510220768601,0.8912510220768601,0.8617021305177772,3.9921913146972656,63.032035
+1632,Multiclass classification,ADWIN Bagging,Keystroke,0.9031269160024524,0.9031269160024524,0.8868998230762756,4.944231986999512,123.60027500000001
+2040,Multiclass classification,ADWIN Bagging,Keystroke,0.898970083374203,0.898970083374203,0.888705938214812,5.993730545043945,211.611387
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+2856,Multiclass classification,ADWIN Bagging,Keystroke,0.8669001751313485,0.8669001751313484,0.8547854134985733,7.318934440612793,479.663409
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+4488,Multiclass classification,ADWIN Bagging,Keystroke,0.8301760641854246,0.8301760641854244,0.8400819204125556,11.044804573059082,1412.144879
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+5712,Multiclass classification,ADWIN Bagging,Keystroke,0.8255997198389073,0.8255997198389075,0.831498100235552,10.513428688049316,2449.732459
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+6528,Multiclass classification,ADWIN Bagging,Keystroke,0.8043511567335683,0.8043511567335683,0.8048077550156274,12.298343658447266,3295.046229
+6936,Multiclass classification,ADWIN Bagging,Keystroke,0.8002883922134102,0.8002883922134101,0.8062362865697692,11.726844787597656,3768.4733180000003
+7344,Multiclass classification,ADWIN Bagging,Keystroke,0.8093422306959008,0.8093422306959008,0.813125473572493,9.433514595031738,4267.304275
+7752,Multiclass classification,ADWIN Bagging,Keystroke,0.8157657076506257,0.8157657076506257,0.8184378776785012,10.539642333984375,4791.9677950000005
+8160,Multiclass classification,ADWIN Bagging,Keystroke,0.8199534256649099,0.81995342566491,0.8213128379144453,11.364830017089844,5345.1630700000005
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+8976,Multiclass classification,ADWIN Bagging,Keystroke,0.8295264623955432,0.8295264623955433,0.8318915513040454,13.833264350891113,6547.972923
+9384,Multiclass classification,ADWIN Bagging,Keystroke,0.8319300863263348,0.8319300863263348,0.8336463894938194,14.741169929504395,7204.877164
+9792,Multiclass classification,ADWIN Bagging,Keystroke,0.8342355224185476,0.8342355224185476,0.8362542817352725,16.02083969116211,7900.9214680000005
+10200,Multiclass classification,ADWIN Bagging,Keystroke,0.8343955289734287,0.8343955289734286,0.833886744496364,17.251243591308594,8638.28045
+10608,Multiclass classification,ADWIN Bagging,Keystroke,0.8258697086829452,0.8258697086829452,0.823298887298616,18.484009742736816,9418.818077
+11016,Multiclass classification,ADWIN Bagging,Keystroke,0.825692237857467,0.825692237857467,0.827229896548608,17.053231239318848,10241.512178
+11424,Multiclass classification,ADWIN Bagging,Keystroke,0.8263153287227524,0.8263153287227524,0.8251000136898328,18.097841262817383,11105.510711
+11832,Multiclass classification,ADWIN Bagging,Keystroke,0.8257966359563857,0.8257966359563859,0.8251092059206939,19.1904354095459,12012.672379000001
+12240,Multiclass classification,ADWIN Bagging,Keystroke,0.8289892965111528,0.8289892965111528,0.8300645161883343,17.2155818939209,12963.554855000002
+12648,Multiclass classification,ADWIN Bagging,Keystroke,0.8324503834901558,0.8324503834901558,0.8328446288662702,17.090572357177734,13955.688030000003
+13056,Multiclass classification,ADWIN Bagging,Keystroke,0.8295672156261968,0.8295672156261968,0.8279815503081916,18.284998893737793,14990.870602000003
+13464,Multiclass classification,ADWIN Bagging,Keystroke,0.828121518235163,0.828121518235163,0.8279872572314477,18.759904861450195,16071.989638000003
+13872,Multiclass classification,ADWIN Bagging,Keystroke,0.8300771393554899,0.8300771393554899,0.8300312724960401,19.937789916992188,17198.739284000003
+14280,Multiclass classification,ADWIN Bagging,Keystroke,0.8329714966034036,0.8329714966034036,0.8330653900337638,21.172300338745117,18373.548754000003
+14688,Multiclass classification,ADWIN Bagging,Keystroke,0.8360454823994008,0.8360454823994008,0.8362319050195895,22.12139320373535,19591.296889000005
+15096,Multiclass classification,ADWIN Bagging,Keystroke,0.8391520370983769,0.8391520370983769,0.8393677597260801,22.688467979431152,20852.364231000003
+15504,Multiclass classification,ADWIN Bagging,Keystroke,0.8400309617493389,0.8400309617493388,0.8398031059873,23.806550979614258,22157.639176000004
+15912,Multiclass classification,ADWIN Bagging,Keystroke,0.8335114072025642,0.8335114072025642,0.8310693286634668,25.06292724609375,23499.792247000005
+16320,Multiclass classification,ADWIN Bagging,Keystroke,0.8283595808566702,0.8283595808566702,0.826721014765785,26.060873985290527,24886.958001000006
+16728,Multiclass classification,ADWIN Bagging,Keystroke,0.826747175225683,0.8267471752256829,0.8259678903415486,27.245673179626465,26317.085564000008
+17136,Multiclass classification,ADWIN Bagging,Keystroke,0.821943390720747,0.821943390720747,0.8202405231953956,28.675668716430664,27793.820666000007
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+17952,Multiclass classification,ADWIN Bagging,Keystroke,0.81878446883182,0.81878446883182,0.8179349229322325,30.879840850830078,30892.431607000006
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+15840,Multiclass classification,AdaBoost,Insects,0.5705536965717533,0.5705536965717533,0.5545059657048704,6.473974227905273,7193.860588999999
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+17952,Multiclass classification,AdaBoost,Insects,0.5307225224221492,0.5307225224221492,0.5138536287616571,6.474637985229492,8952.059017
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+21120,Multiclass classification,AdaBoost,Insects,0.5272503432927695,0.5272503432927695,0.5067114684709674,15.437758445739746,11917.076256
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+28512,Multiclass classification,AdaBoost,Insects,0.5692890463329943,0.5692890463329943,0.5455529487931667,17.26294231414795,20283.404340999998
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+41184,Multiclass classification,AdaBoost,Insects,0.5417769467984362,0.5417769467984362,0.5296361895775551,23.860816955566406,38464.674338
+42240,Multiclass classification,AdaBoost,Insects,0.5422240109851085,0.5422240109851085,0.5313111510734391,24.196860313415527,40175.576412999995
+43296,Multiclass classification,AdaBoost,Insects,0.5444970550871925,0.5444970550871925,0.5344195798463859,24.296037673950195,41906.99288399999
+44352,Multiclass classification,AdaBoost,Insects,0.5463461928705102,0.5463461928705102,0.5369578677381479,24.84640598297119,43659.477484999996
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+2024,Multiclass classification,Bagging,ImageSegments,0.7775580820563519,0.7775580820563519,0.7671264358471986,4.154878616333008,2730.5624909999997
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+4224,Multiclass classification,Bagging,Insects,0.6107032914989344,0.6107032914989344,0.5748501357120321,6.535015106201172,804.5259470000001
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+966,Multiclass classification,Leveraging Bagging,ImageSegments,0.7512953367875648,0.7512953367875648,0.747322646811651,4.099823951721191,1664.8953589999999
+1012,Multiclass classification,Leveraging Bagging,ImageSegments,0.7507418397626113,0.7507418397626113,0.7469783619055548,4.099823951721191,1817.1987969999998
+1058,Multiclass classification,Leveraging Bagging,ImageSegments,0.7530747398297067,0.7530747398297066,0.7482363934596314,4.099823951721191,1975.1124209999998
+1104,Multiclass classification,Leveraging Bagging,ImageSegments,0.7552130553037172,0.7552130553037172,0.750118495060715,4.0998735427856445,2138.658016
+1150,Multiclass classification,Leveraging Bagging,ImageSegments,0.7571801566579635,0.7571801566579635,0.7516199800653577,4.0998735427856445,2307.825702
+1196,Multiclass classification,Leveraging Bagging,ImageSegments,0.7598326359832636,0.7598326359832636,0.7548841797367702,4.0998735427856445,2482.820129
+1242,Multiclass classification,Leveraging Bagging,ImageSegments,0.7598710717163578,0.7598710717163577,0.7553301531902636,4.0998735427856445,2663.4478950000002
+1288,Multiclass classification,Leveraging Bagging,ImageSegments,0.7645687645687645,0.7645687645687647,0.7590078532621816,4.1004838943481445,2849.419913
+1334,Multiclass classification,Leveraging Bagging,ImageSegments,0.7644411102775694,0.7644411102775694,0.7591993978414527,4.100506782531738,3040.9965970000003
+1380,Multiclass classification,Leveraging Bagging,ImageSegments,0.7650471356055112,0.7650471356055112,0.7601575050520947,4.100506782531738,3238.5768190000003
+1426,Multiclass classification,Leveraging Bagging,ImageSegments,0.7670175438596492,0.7670175438596492,0.7613339877221927,4.100506782531738,3441.4807240000005
+1472,Multiclass classification,Leveraging Bagging,ImageSegments,0.7715839564921821,0.7715839564921821,0.7641396475218201,4.100552558898926,3649.5015090000006
+1518,Multiclass classification,Leveraging Bagging,ImageSegments,0.7732366512854317,0.7732366512854317,0.7648275341801108,4.100552558898926,3862.6942700000004
+1564,Multiclass classification,Leveraging Bagging,ImageSegments,0.7735124760076776,0.7735124760076776,0.7657569341108763,4.100552558898926,4080.8910560000004
+1610,Multiclass classification,Leveraging Bagging,ImageSegments,0.7737725295214419,0.7737725295214419,0.7651494083475014,4.1005754470825195,4304.577590000001
+1656,Multiclass classification,Leveraging Bagging,ImageSegments,0.7740181268882175,0.7740181268882175,0.7654813489818475,4.100529670715332,4533.710142000001
+1702,Multiclass classification,Leveraging Bagging,ImageSegments,0.7730746619635509,0.7730746619635509,0.766493027961906,4.100529670715332,4767.793233000001
+1748,Multiclass classification,Leveraging Bagging,ImageSegments,0.7756153405838581,0.7756153405838581,0.7686072256536652,4.100529670715332,5007.029776000001
+1794,Multiclass classification,Leveraging Bagging,ImageSegments,0.7769102063580591,0.7769102063580591,0.7685414235990152,4.100502967834473,5251.440116000002
+1840,Multiclass classification,Leveraging Bagging,ImageSegments,0.7781402936378466,0.7781402936378466,0.7699957723931323,4.100502967834473,5500.964415000001
+1886,Multiclass classification,Leveraging Bagging,ImageSegments,0.7761273209549071,0.7761273209549071,0.7684985598909853,4.100502967834473,5755.503987000001
+1932,Multiclass classification,Leveraging Bagging,ImageSegments,0.7762817193164163,0.7762817193164163,0.7677434418046419,4.100502967834473,6014.862306000001
+1978,Multiclass classification,Leveraging Bagging,ImageSegments,0.7774405665149215,0.7774405665149215,0.7684788817649146,4.100502967834473,6279.121569000001
+2024,Multiclass classification,Leveraging Bagging,ImageSegments,0.7790410281759763,0.7790410281759763,0.7689103339153599,4.100502967834473,6548.278113000001
+2070,Multiclass classification,Leveraging Bagging,ImageSegments,0.7786370227162881,0.7786370227162881,0.7686288077529282,4.100502967834473,6822.363214000001
+2116,Multiclass classification,Leveraging Bagging,ImageSegments,0.7791962174940898,0.7791962174940898,0.768391950800897,4.100502967834473,7101.096348000001
+2162,Multiclass classification,Leveraging Bagging,ImageSegments,0.7801943544655252,0.7801943544655253,0.768962628827985,4.100525856018066,7384.333285000001
+2208,Multiclass classification,Leveraging Bagging,ImageSegments,0.7820570910738559,0.7820570910738559,0.7698068761587117,4.100499153137207,7672.298476000001
+2254,Multiclass classification,Leveraging Bagging,ImageSegments,0.7789613848202397,0.7789613848202397,0.7667173742344939,4.100499153137207,7965.117559000001
+2300,Multiclass classification,Leveraging Bagging,ImageSegments,0.7781644193127447,0.7781644193127447,0.7659138381656089,4.100499153137207,8262.647904000001
+2310,Multiclass classification,Leveraging Bagging,ImageSegments,0.7782589865742746,0.7782589865742745,0.7660163657276376,4.100499153137207,8561.303246000001
+1056,Multiclass classification,Leveraging Bagging,Insects,0.6218009478672986,0.6218009478672986,0.5857016652718549,6.471495628356934,220.837673
+2112,Multiclass classification,Leveraging Bagging,Insects,0.6196115585030791,0.6196115585030791,0.5856756432415233,10.302834510803223,598.297395
+3168,Multiclass classification,Leveraging Bagging,Insects,0.628986422481844,0.628986422481844,0.5949930595607559,19.024110794067383,1103.516793
+4224,Multiclass classification,Leveraging Bagging,Insects,0.6294103717736207,0.6294103717736207,0.5952675443708706,19.52926254272461,1735.893967
+5280,Multiclass classification,Leveraging Bagging,Insects,0.6364841826103429,0.6364841826103429,0.5994911272790603,18.82306957244873,2497.807238
+6336,Multiclass classification,Leveraging Bagging,Insects,0.6352012628255722,0.6352012628255722,0.5993891820807258,20.00343894958496,3379.788115
+7392,Multiclass classification,Leveraging Bagging,Insects,0.638749830875389,0.638749830875389,0.6030343276880051,20.9547061920166,4385.582643
+8448,Multiclass classification,Leveraging Bagging,Insects,0.6405824553095774,0.6405824553095774,0.6028521616895871,23.98197650909424,5520.259032
+9504,Multiclass classification,Leveraging Bagging,Insects,0.6449542249815847,0.6449542249815847,0.6055705492028415,24.687146186828613,6764.141036999999
+10560,Multiclass classification,Leveraging Bagging,Insects,0.6485462638507434,0.6485462638507434,0.6081614166360887,28.76917839050293,8102.806145
+11616,Multiclass classification,Leveraging Bagging,Insects,0.6490744726646578,0.6490744726646578,0.6078786452761632,30.803756713867188,9530.02909
+12672,Multiclass classification,Leveraging Bagging,Insects,0.6514876489621971,0.6514876489621971,0.6111938480023122,35.14385414123535,11044.697830000001
+13728,Multiclass classification,Leveraging Bagging,Insects,0.6707947840023312,0.6707947840023312,0.6607574394823457,17.51351547241211,12617.098737
+14784,Multiclass classification,Leveraging Bagging,Insects,0.6821348846648176,0.6821348846648176,0.6733632096765088,9.275564193725586,14250.678949000001
+15840,Multiclass classification,Leveraging Bagging,Insects,0.6778205694803965,0.6778205694803965,0.670556396248407,11.964457511901855,15956.730999000001
+16896,Multiclass classification,Leveraging Bagging,Insects,0.6754661142349808,0.6754661142349808,0.6690281338426608,12.60369873046875,17732.973803
+17952,Multiclass classification,Leveraging Bagging,Insects,0.6721631106902123,0.6721631106902123,0.6660357480506892,12.93508529663086,19577.321708
+19008,Multiclass classification,Leveraging Bagging,Insects,0.6856947440416689,0.6856947440416689,0.6751812770122833,14.563780784606934,21465.395048
+20064,Multiclass classification,Leveraging Bagging,Insects,0.6926680954991776,0.6926680954991776,0.6785701715539604,23.61655616760254,23398.659989
+21120,Multiclass classification,Leveraging Bagging,Insects,0.6942090061082438,0.6942090061082438,0.6784920731228882,30.020954132080078,25401.280766
+22176,Multiclass classification,Leveraging Bagging,Insects,0.6958737316798196,0.6958737316798196,0.6784853924286285,31.293453216552734,27443.688764
+23232,Multiclass classification,Leveraging Bagging,Insects,0.6989798114588266,0.6989798114588266,0.6799590657327791,29.59604263305664,29526.276676999998
+24288,Multiclass classification,Leveraging Bagging,Insects,0.7011981718614897,0.7011981718614897,0.680282364066019,32.615909576416016,31645.669427999997
+25344,Multiclass classification,Leveraging Bagging,Insects,0.7031527443475516,0.7031527443475516,0.6805566439417602,33.91432285308838,33792.819539
+26400,Multiclass classification,Leveraging Bagging,Insects,0.7051782264479716,0.7051782264479716,0.6809495737401271,35.12977695465088,35966.301701
+27456,Multiclass classification,Leveraging Bagging,Insects,0.7065743944636678,0.7065743944636678,0.6805936316849747,38.84447956085205,38159.78466
+28512,Multiclass classification,Leveraging Bagging,Insects,0.7054820946301428,0.7054820946301428,0.681225779493031,34.570815086364746,40377.715598999996
+29568,Multiclass classification,Leveraging Bagging,Insects,0.7045692833226231,0.7045692833226231,0.6849598194839713,20.382534980773926,42611.23284999999
+30624,Multiclass classification,Leveraging Bagging,Insects,0.7031316330862424,0.7031316330862424,0.6877640955933652,22.55568027496338,44864.71640799999
+31680,Multiclass classification,Leveraging Bagging,Insects,0.7032418952618454,0.7032418952618454,0.6917227552448634,26.177990913391113,47133.482559
+32736,Multiclass classification,Leveraging Bagging,Insects,0.7037421719871697,0.7037421719871697,0.6952024388211077,25.761178016662598,49415.922784999995
+33792,Multiclass classification,Leveraging Bagging,Insects,0.7002160338551685,0.7002160338551685,0.6931280234945141,25.958494186401367,51714.47139399999
+34848,Multiclass classification,Leveraging Bagging,Insects,0.6973627571957414,0.6973627571957414,0.6902163957562899,18.894118309020996,54032.337051999995
+35904,Multiclass classification,Leveraging Bagging,Insects,0.6951786758766677,0.6951786758766677,0.6877287571005829,18.049145698547363,56371.370632
+36960,Multiclass classification,Leveraging Bagging,Insects,0.6919830081982737,0.6919830081982737,0.6843647347906762,22.045016288757324,58731.919307
+38016,Multiclass classification,Leveraging Bagging,Insects,0.6900697093252663,0.6900697093252663,0.68217396069655,25.079078674316406,61114.705623999995
+39072,Multiclass classification,Leveraging Bagging,Insects,0.688720534411712,0.688720534411712,0.6808510434728485,19.794261932373047,63520.517782999996
+40128,Multiclass classification,Leveraging Bagging,Insects,0.6867695068158597,0.6867695068158597,0.6796002866264578,10.854747772216797,65948.78476699999
+41184,Multiclass classification,Leveraging Bagging,Insects,0.6843843333414273,0.6843843333414273,0.6779529807793833,10.474969863891602,68395.63477799999
+42240,Multiclass classification,Leveraging Bagging,Insects,0.6822131205757712,0.6822131205757712,0.6764872431583758,14.707494735717773,70864.05938699999
+43296,Multiclass classification,Leveraging Bagging,Insects,0.6795472918350849,0.6795472918350849,0.674587653669649,12.672552108764648,73351.02096199998
+44352,Multiclass classification,Leveraging Bagging,Insects,0.6769633153705666,0.6769633153705666,0.6725984110786069,13.144417762756348,75857.66838799998
+45408,Multiclass classification,Leveraging Bagging,Insects,0.6748959411544475,0.6748959411544475,0.6710316194917795,14.719610214233398,78383.45415699997
+46464,Multiclass classification,Leveraging Bagging,Insects,0.6743215031315241,0.6743215031315241,0.670959098678123,15.027325630187988,80927.72302099997
+47520,Multiclass classification,Leveraging Bagging,Insects,0.6765293882447021,0.6765293882447021,0.6733002712216741,17.283148765563965,83488.02074099997
+48576,Multiclass classification,Leveraging Bagging,Insects,0.6805970149253732,0.6805970149253732,0.6770692638556323,17.906007766723633,86063.52222099998
+49632,Multiclass classification,Leveraging Bagging,Insects,0.6848340754770205,0.6848340754770205,0.6808344811077705,18.8202543258667,88653.18323199998
+50688,Multiclass classification,Leveraging Bagging,Insects,0.6890524197525992,0.6890524197525992,0.6843657264244208,21.507144927978516,91255.74433499998
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+52800,Multiclass classification,Leveraging Bagging,Insects,0.6956002954601412,0.6956002954601412,0.6902433463100389,14.128369331359863,96495.21656399999
+52848,Multiclass classification,Leveraging Bagging,Insects,0.6958578538043787,0.6958578538043787,0.6905081705907102,13.831001281738281,99120.19143899999
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+1632,Multiclass classification,Leveraging Bagging,Keystroke,0.9589209074187615,0.9589209074187615,0.9361222534860761,8.122180938720703,291.606081
+2040,Multiclass classification,Leveraging Bagging,Keystroke,0.9573320255026974,0.9573320255026974,0.9445755787125868,10.5212984085083,455.912148
+2448,Multiclass classification,Leveraging Bagging,Keystroke,0.9607682876992235,0.9607682876992235,0.9588299190873342,9.065413475036621,649.921126
+2856,Multiclass classification,Leveraging Bagging,Keystroke,0.9618213660245184,0.9618213660245184,0.9516555143941907,13.188368797302246,870.236672
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+3672,Multiclass classification,Leveraging Bagging,Keystroke,0.9585943884500137,0.9585943884500137,0.9531276848185062,16.65507411956787,1406.732623
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+4488,Multiclass classification,Leveraging Bagging,Keystroke,0.9529752618676176,0.9529752618676176,0.9549694463549354,10.336687088012695,2070.686487
+4896,Multiclass classification,Leveraging Bagging,Keystroke,0.9550561797752809,0.9550561797752809,0.95517907029875,11.520882606506348,2449.358224
+5304,Multiclass classification,Leveraging Bagging,Keystroke,0.9568168960965491,0.9568168960965491,0.9575833276239932,13.737529754638672,2856.6015070000003
+5712,Multiclass classification,Leveraging Bagging,Keystroke,0.9574505340570828,0.9574505340570828,0.9570632809827344,15.842782020568848,3290.691514
+6120,Multiclass classification,Leveraging Bagging,Keystroke,0.9557117176009152,0.9557117176009152,0.9522483041543378,20.042810440063477,3760.43818
+6528,Multiclass classification,Leveraging Bagging,Keystroke,0.9566416424084572,0.9566416424084572,0.9568246790885271,11.687369346618652,4258.095146
+6936,Multiclass classification,Leveraging Bagging,Keystroke,0.9574621485219899,0.9574621485219899,0.9579855320572277,12.487288475036621,4780.363237
+7344,Multiclass classification,Leveraging Bagging,Keystroke,0.9568296336647147,0.9568296336647147,0.9563404233689646,15.327423095703125,5334.336646
+7752,Multiclass classification,Leveraging Bagging,Keystroke,0.9565217391304348,0.9565217391304348,0.9563017119581124,18.70553493499756,5920.99825
+8160,Multiclass classification,Leveraging Bagging,Keystroke,0.9545287412673121,0.9545287412673121,0.9527980459948603,24.086796760559082,6539.621381999999
+8568,Multiclass classification,Leveraging Bagging,Keystroke,0.9545932064900199,0.9545932064900199,0.9549210113442089,21.21516990661621,7187.28418
+8976,Multiclass classification,Leveraging Bagging,Keystroke,0.9550974930362117,0.9550974930362117,0.9553627160759579,17.566545486450195,7867.8027329999995
+9384,Multiclass classification,Leveraging Bagging,Keystroke,0.9555579239049344,0.9555579239049344,0.9558253322166266,15.710055351257324,8578.363562999999
+9792,Multiclass classification,Leveraging Bagging,Keystroke,0.9552650393218262,0.9552650393218262,0.9553715117788079,18.717252731323242,9321.146735999999
+10200,Multiclass classification,Leveraging Bagging,Keystroke,0.9533287577213452,0.9533287577213452,0.9523119157834915,15.605277061462402,10099.276789999998
+10608,Multiclass classification,Leveraging Bagging,Keystroke,0.9521070990855096,0.9521070990855096,0.9515822083565743,11.186952590942383,10903.979313999998
+11016,Multiclass classification,Leveraging Bagging,Keystroke,0.953427144802542,0.953427144802542,0.9541201209142027,7.581887245178223,11728.435273
+11424,Multiclass classification,Leveraging Bagging,Keystroke,0.953689923837871,0.953689923837871,0.9538275342826803,10.15964126586914,12573.844722999998
+11832,Multiclass classification,Leveraging Bagging,Keystroke,0.9535964838137098,0.9535964838137098,0.9538502960885477,11.061944961547852,13441.174568999999
+12240,Multiclass classification,Leveraging Bagging,Keystroke,0.9541629218073372,0.9541629218073372,0.9544632162431566,11.249642372131348,14331.138910999998
+12648,Multiclass classification,Leveraging Bagging,Keystroke,0.9548509527951293,0.9548509527951293,0.9551609875055331,13.203255653381348,15243.410521999998
+13056,Multiclass classification,Leveraging Bagging,Keystroke,0.9551895825354271,0.955189582535427,0.9553883557595891,9.36058521270752,16176.429406999998
+13464,Multiclass classification,Leveraging Bagging,Keystroke,0.955953353635891,0.955953353635891,0.9562606797905644,11.575583457946777,17130.275872
+13872,Multiclass classification,Leveraging Bagging,Keystroke,0.9561675437964098,0.9561675437964098,0.9563487774281333,11.42638874053955,18106.072389999998
+14280,Multiclass classification,Leveraging Bagging,Keystroke,0.9549688353526157,0.9549688353526157,0.9548529395574759,10.249165534973145,19109.380900999997
+14688,Multiclass classification,Leveraging Bagging,Keystroke,0.9552665622659495,0.9552665622659495,0.955472434271787,8.168793678283691,20137.264238999996
+15096,Multiclass classification,Leveraging Bagging,Keystroke,0.9560781715799934,0.9560781715799934,0.9563263247313607,9.020037651062012,21191.151532999997
+15504,Multiclass classification,Leveraging Bagging,Keystroke,0.9563955363478036,0.9563955363478036,0.9565429512012837,8.031278610229492,22273.408126999995
+15912,Multiclass classification,Leveraging Bagging,Keystroke,0.9566337753755264,0.9566337753755264,0.9567672375037608,10.967172622680664,23379.117397999995
+16320,Multiclass classification,Leveraging Bagging,Keystroke,0.9563085973405233,0.9563085973405233,0.9563585840602682,11.29026985168457,24508.785403999995
+16728,Multiclass classification,Leveraging Bagging,Keystroke,0.955580797513003,0.955580797513003,0.9555776398983683,9.525394439697266,25660.924918999994
+17136,Multiclass classification,Leveraging Bagging,Keystroke,0.9564050189670266,0.9564050189670267,0.9565585833577668,10.421767234802246,26839.493165999993
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+1104,Multiclass classification,Stacking,ImageSegments,0.8213961922030825,0.8213961922030824,0.8206569542548617,8.760258674621582,1267.2341280000003
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+7344,Multiclass classification,Stacking,Keystroke,0.9765763311997822,0.9765763311997822,0.9763923596721359,12.33658504486084,5881.2072339999995
+7752,Multiclass classification,Stacking,Keystroke,0.9771642368726616,0.9771642368726616,0.9773496343719735,13.116165161132812,6492.775159
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+9792,Multiclass classification,Stacking,Keystroke,0.9765090389132877,0.9765090389132877,0.9763153416047449,16.169885635375977,10037.443626
+10200,Multiclass classification,Stacking,Keystroke,0.9758799882341406,0.9758799882341406,0.9755246287395946,14.205968856811523,10844.068015
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+13056,Multiclass classification,Stacking,Keystroke,0.9758713136729222,0.9758713136729221,0.975797420384815,15.049361228942871,17460.942559000003
+13464,Multiclass classification,Stacking,Keystroke,0.9757112084973631,0.9757112084973631,0.9757165619520196,15.162266731262207,18558.798501
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+14280,Multiclass classification,Stacking,Keystroke,0.9754884795854052,0.9754884795854052,0.975424480421301,16.988737106323242,20872.643227
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+15096,Multiclass classification,Stacking,Keystroke,0.9757535607817158,0.9757535607817158,0.9758249143111629,17.579912185668945,23330.568569000003
+15504,Multiclass classification,Stacking,Keystroke,0.9755531187512094,0.9755531187512094,0.9755669148190674,16.59157657623291,24610.336028
+15912,Multiclass classification,Stacking,Keystroke,0.9756772044497517,0.9756772044497517,0.9757389077528199,16.193113327026367,25925.188427
+16320,Multiclass classification,Stacking,Keystroke,0.9759176420123782,0.9759176420123782,0.9759886766110538,16.353660583496094,27266.573062
+16728,Multiclass classification,Stacking,Keystroke,0.9756680815448078,0.9756680815448078,0.9756766431570708,17.00908374786377,28641.859399
+17136,Multiclass classification,Stacking,Keystroke,0.9758389261744966,0.9758389261744966,0.975891563489883,18.364989280700684,30047.550521
+17544,Multiclass classification,Stacking,Keystroke,0.9753747933648749,0.9753747933648749,0.975363882573194,17.298136711120605,31485.782589000002
+17952,Multiclass classification,Stacking,Keystroke,0.9753217090969862,0.9753217090969862,0.9753429667022142,16.72727108001709,32956.927282000004
+18360,Multiclass classification,Stacking,Keystroke,0.9754888610490767,0.9754888610490767,0.9755190387029732,17.51059913635254,34461.639008000006
+18768,Multiclass classification,Stacking,Keystroke,0.9757553151809026,0.9757553151809026,0.9757835195290103,18.871691703796387,35998.873267
+19176,Multiclass classification,Stacking,Keystroke,0.9754367666232073,0.9754367666232073,0.9754369138844643,17.42948341369629,37568.082084
+19584,Multiclass classification,Stacking,Keystroke,0.9754889444926722,0.9754889444926722,0.9754964783302286,17.978480339050293,39170.395427
+19992,Multiclass classification,Stacking,Keystroke,0.9756390375669051,0.9756390375669051,0.975642520227376,19.26256561279297,40805.125646
+20400,Multiclass classification,Stacking,Keystroke,0.9754889945585568,0.9754889945585568,0.9754863274548964,18.711057662963867,42471.761869
+46,Multiclass classification,Voting,ImageSegments,0.4666666666666667,0.4666666666666667,0.3890768588137009,0.9137420654296875,0.663852
+92,Multiclass classification,Voting,ImageSegments,0.6153846153846154,0.6153846153846154,0.617040786788686,0.9906883239746094,2.032737
+138,Multiclass classification,Voting,ImageSegments,0.6715328467153284,0.6715328467153284,0.6884491245817251,1.0679149627685547,4.226265
+184,Multiclass classification,Voting,ImageSegments,0.7049180327868853,0.7049180327868853,0.7194266051408907,1.1443958282470703,7.386208
+230,Multiclass classification,Voting,ImageSegments,0.7292576419213974,0.7292576419213974,0.7448338459304749,1.2214689254760742,11.723904000000001
+276,Multiclass classification,Voting,ImageSegments,0.7381818181818182,0.7381818181818182,0.7559766728000937,1.2995519638061523,17.331033
+322,Multiclass classification,Voting,ImageSegments,0.7538940809968847,0.7538940809968847,0.7616248500949714,1.3766565322875977,24.26159
+368,Multiclass classification,Voting,ImageSegments,0.773841961852861,0.7738419618528611,0.7772939373537765,1.4532833099365234,32.770568000000004
+414,Multiclass classification,Voting,ImageSegments,0.7820823244552058,0.7820823244552059,0.7854200812154107,1.5304145812988281,42.983195
+460,Multiclass classification,Voting,ImageSegments,0.7777777777777778,0.7777777777777778,0.7796254955467015,1.6075658798217773,54.886431
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+552,Multiclass classification,Voting,ImageSegments,0.7858439201451906,0.7858439201451906,0.7889431335032357,4.088808059692383,121.00394599999998
+598,Multiclass classification,Voting,ImageSegments,0.7906197654941374,0.7906197654941374,0.7944387660679091,4.304059028625488,157.00397999999998
+644,Multiclass classification,Voting,ImageSegments,0.7853810264385692,0.7853810264385692,0.7901251252871709,4.532710075378418,195.073691
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+736,Multiclass classification,Voting,ImageSegments,0.7863945578231293,0.7863945578231294,0.7911065855691086,4.991429328918457,277.59961999999996
+782,Multiclass classification,Voting,ImageSegments,0.7887323943661971,0.7887323943661971,0.792926322670609,5.219735145568848,322.07131499999997
+828,Multiclass classification,Voting,ImageSegments,0.7896009673518742,0.7896009673518742,0.7950712422059908,5.452417373657227,368.82718
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+966,Multiclass classification,Voting,ImageSegments,0.7937823834196891,0.7937823834196891,0.7958827691316667,6.182188987731934,522.9385980000001
+1012,Multiclass classification,Voting,ImageSegments,0.7912957467853611,0.7912957467853611,0.7931630938612351,6.34267520904541,579.2700850000001
+1058,Multiclass classification,Voting,ImageSegments,0.793755912961211,0.7937559129612108,0.7947921362588558,6.295009613037109,638.2805060000001
+1104,Multiclass classification,Voting,ImageSegments,0.7941976427923844,0.7941976427923844,0.7951664828862093,6.2213640213012695,699.725726
+1150,Multiclass classification,Voting,ImageSegments,0.7954743255004352,0.7954743255004351,0.7958304956922065,6.151959419250488,763.5071
+1196,Multiclass classification,Voting,ImageSegments,0.796652719665272,0.796652719665272,0.7972397572733622,6.087224006652832,829.5043310000001
+1242,Multiclass classification,Voting,ImageSegments,0.7953263497179693,0.7953263497179693,0.795947547023496,6.001987457275391,897.6078460000001
+1288,Multiclass classification,Voting,ImageSegments,0.7995337995337995,0.7995337995337995,0.799082939294124,5.924266815185547,967.7224320000001
+1334,Multiclass classification,Voting,ImageSegments,0.7981995498874719,0.7981995498874719,0.7978549794399667,5.872907638549805,1039.926656
+1380,Multiclass classification,Voting,ImageSegments,0.7991298042059464,0.7991298042059464,0.799072028035076,5.784454345703125,1114.0085680000002
+1426,Multiclass classification,Voting,ImageSegments,0.8007017543859649,0.8007017543859649,0.799801266098334,5.781437873840332,1190.125915
+1472,Multiclass classification,Voting,ImageSegments,0.8042148198504419,0.8042148198504419,0.8016037490391381,5.805401802062988,1268.322504
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+1610,Multiclass classification,Voting,ImageSegments,0.8048477315102548,0.8048477315102549,0.8009666848419111,6.138180732727051,1517.316045
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+1702,Multiclass classification,Voting,ImageSegments,0.8048206937095826,0.8048206937095828,0.802987300619633,6.14796257019043,1694.105126
+1748,Multiclass classification,Voting,ImageSegments,0.8065254722381225,0.8065254722381225,0.8041280306488863,6.185528755187988,1785.6451299999999
+1794,Multiclass classification,Voting,ImageSegments,0.8070273284997211,0.8070273284997211,0.8033862119520573,6.18717098236084,1879.2213629999999
+1840,Multiclass classification,Voting,ImageSegments,0.8085916258836324,0.8085916258836324,0.8051706679397826,6.228180885314941,1974.8859899999998
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+2024,Multiclass classification,Voting,ImageSegments,0.8096885813148789,0.809688581314879,0.8043903689108628,6.209332466125488,2378.336668
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+2300,Multiclass classification,Voting,ImageSegments,0.8064375815571988,0.8064375815571988,0.7990276111502428,6.073050498962402,3041.734776
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+1056,Multiclass classification,Voting,Insects,0.6293838862559241,0.6293838862559241,0.5938169901557457,7.681754112243652,78.197886
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+9504,Multiclass classification,Voting,Insects,0.6255919183415763,0.6255919183415763,0.5892477749449755,7.551809310913086,2416.671036
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+12672,Multiclass classification,Voting,Insects,0.6276536974193039,0.6276536974193039,0.5948280902959312,7.593076705932617,3891.533291
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+15840,Multiclass classification,Voting,Insects,0.6042048109097796,0.6042048109097796,0.5876183517420878,7.622871398925781,5663.9066330000005
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+19008,Multiclass classification,Voting,Insects,0.5655811016993739,0.5655811016993739,0.5465928919365096,7.569133758544922,7739.601247
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+21120,Multiclass classification,Voting,Insects,0.5817510298783086,0.5817510298783086,0.55937505855693,8.13927173614502,9285.092110999998
+22176,Multiclass classification,Voting,Insects,0.5905298759864712,0.5905298759864712,0.5668099949242361,8.13715648651123,10104.551325999999
+23232,Multiclass classification,Voting,Insects,0.6004907236020834,0.6004907236020834,0.5756153967719769,8.254791259765625,10955.282647999999
+24288,Multiclass classification,Voting,Insects,0.6088854119487792,0.6088854119487792,0.5822871692574689,8.217899322509766,11836.441737999998
+25344,Multiclass classification,Voting,Insects,0.617014560233595,0.617014560233595,0.5890646667396601,8.13050651550293,12747.590801999997
+26400,Multiclass classification,Voting,Insects,0.6237357475661957,0.6237357475661957,0.5942060376379845,8.178851127624512,13688.250944999996
+27456,Multiclass classification,Voting,Insects,0.6299763248952832,0.6299763248952832,0.5983574644866619,8.215079307556152,14661.447404999995
+28512,Multiclass classification,Voting,Insects,0.6312651257409421,0.6312651257409421,0.6016879522351425,8.160200119018555,15669.084531999995
+29568,Multiclass classification,Voting,Insects,0.6310751851726587,0.6310751851726587,0.6062390002054064,8.153844833374023,16709.899933999994
+30624,Multiclass classification,Voting,Insects,0.6313228619011854,0.6313228619011854,0.610710416812842,8.221953392028809,17785.196262999994
+31680,Multiclass classification,Voting,Insects,0.6320590927743931,0.6320590927743931,0.614817700164209,8.237210273742676,18894.010558999995
+32736,Multiclass classification,Voting,Insects,0.6331144035436077,0.6331144035436077,0.6184679282473909,8.208189964294434,20033.816622999995
+33792,Multiclass classification,Voting,Insects,0.6291616110798733,0.6291616110798733,0.6151628967287334,8.149331092834473,21206.789184999994
+34848,Multiclass classification,Voting,Insects,0.6245587855482538,0.6245587855482538,0.6103108800280445,8.270771980285645,22409.569843999994
+35904,Multiclass classification,Voting,Insects,0.6211737180736986,0.6211737180736986,0.6063163580543118,8.246885299682617,23639.112908999996
+36960,Multiclass classification,Voting,Insects,0.6171433209772992,0.6171433209772992,0.6018416894357856,8.222872734069824,24895.212450999996
+38016,Multiclass classification,Voting,Insects,0.6153360515585953,0.6153360515585953,0.5996210858832133,8.711487770080566,26177.407049999994
+39072,Multiclass classification,Voting,Insects,0.613472908295155,0.613472908295155,0.5980758777202522,8.84398365020752,27486.887242999994
+40128,Multiclass classification,Voting,Insects,0.6139008647544048,0.6139008647544048,0.5993833357378361,9.00393295288086,28821.579146999993
+41184,Multiclass classification,Voting,Insects,0.6157395041643396,0.6157395041643396,0.6018873090815099,8.895415306091309,30174.675792999995
+42240,Multiclass classification,Voting,Insects,0.6179833802883591,0.6179833802883591,0.6047393094362844,8.820836067199707,31551.592344999994
+43296,Multiclass classification,Voting,Insects,0.6202101859337106,0.6202101859337106,0.60743097275183,8.80302619934082,32950.21258099999
+44352,Multiclass classification,Voting,Insects,0.6221054767648982,0.6221054767648982,0.6097047537791253,8.807188034057617,34370.71930599999
+45408,Multiclass classification,Voting,Insects,0.623736428304006,0.623736428304006,0.6112415003179203,8.906554222106934,35814.22252799999
+46464,Multiclass classification,Voting,Insects,0.6259389191399608,0.6259389191399608,0.6133867892257391,8.822076797485352,37279.498286999995
+47520,Multiclass classification,Voting,Insects,0.6274542814453166,0.6274542814453166,0.6153714367024555,8.875716209411621,38770.246245999995
+48576,Multiclass classification,Voting,Insects,0.6317858980957283,0.6317858980957283,0.6202967225132047,8.86828327178955,40284.403256
+49632,Multiclass classification,Voting,Insects,0.6360137817090125,0.6360137817090125,0.6247992459885968,8.835649490356445,41820.805007999996
+50688,Multiclass classification,Voting,Insects,0.6403811628228145,0.6403811628228145,0.6293790828873279,8.924153327941895,43378.957976
+51744,Multiclass classification,Voting,Insects,0.6455559206076185,0.6455559206076185,0.6346828420183047,9.218049049377441,44959.107880999996
+52800,Multiclass classification,Voting,Insects,0.648269853595712,0.648269853595712,0.6377385869395499,9.400546073913574,46560.782
+52848,Multiclass classification,Voting,Insects,0.6485325562472799,0.6485325562472799,0.637999701607352,9.406517028808594,48163.738895
+408,Multiclass classification,Voting,Keystroke,0.9828009828009828,0.9828009828009828,0.6067632850241546,1.4587059020996094,10.139614
+816,Multiclass classification,Voting,Keystroke,0.9496932515337423,0.9496932515337423,0.7435135353411919,6.019382476806641,66.737739
+1224,Multiclass classification,Voting,Keystroke,0.9149632052330335,0.9149632052330335,0.9012024099743488,7.076447486877441,151.07716299999998
+1632,Multiclass classification,Voting,Keystroke,0.9258123850398529,0.9258123850398529,0.913338738884437,7.232892990112305,261.540164
+2040,Multiclass classification,Voting,Keystroke,0.9230014713094654,0.9230014713094654,0.9086113906821328,7.553393363952637,397.83621500000004
+2448,Multiclass classification,Voting,Keystroke,0.8961994278708623,0.8961994278708623,0.8992132713257572,7.640434265136719,558.733108
+2856,Multiclass classification,Voting,Keystroke,0.9001751313485113,0.9001751313485113,0.8860451027148403,7.9326982498168945,743.600486
+3264,Multiclass classification,Voting,Keystroke,0.8924302788844621,0.8924302788844621,0.8761196773917237,8.074724197387695,952.077233
+3672,Multiclass classification,Voting,Keystroke,0.8874965949332607,0.8874965949332607,0.8846937712308092,8.20841121673584,1184.393658
+4080,Multiclass classification,Voting,Keystroke,0.8815886246629075,0.8815886246629075,0.868452721773406,8.525882720947266,1441.2089369999999
+4488,Multiclass classification,Voting,Keystroke,0.8760864720303098,0.8760864720303098,0.8834419600614621,8.681946754455566,1719.7568239999998
+4896,Multiclass classification,Voting,Keystroke,0.8737487231869254,0.8737487231869254,0.8797220914000274,8.834684371948242,2018.9742069999998
+5304,Multiclass classification,Voting,Keystroke,0.8693192532528757,0.8693192532528757,0.8538682361373632,9.067034721374512,2339.6996679999997
+5712,Multiclass classification,Voting,Keystroke,0.8607949571003327,0.8607949571003327,0.8654889627515672,9.271133422851562,2680.904224
+6120,Multiclass classification,Voting,Keystroke,0.8561856512502043,0.8561856512502043,0.84095068957581,9.378315925598145,3042.663698
+6528,Multiclass classification,Voting,Keystroke,0.8434196414891987,0.8434196414891987,0.8427350578509161,9.608606338500977,3424.478417
+6936,Multiclass classification,Voting,Keystroke,0.8392213410237923,0.8392213410237923,0.8447429510460126,9.751982688903809,3824.86879
+7344,Multiclass classification,Voting,Keystroke,0.8454310227427482,0.8454310227427482,0.847842289102327,9.957889556884766,4243.00141
+7752,Multiclass classification,Voting,Keystroke,0.8456973293768546,0.8456973293768547,0.8480563212460421,10.19985294342041,4680.993142
+8160,Multiclass classification,Voting,Keystroke,0.8469175144012747,0.8469175144012746,0.8472851046009279,10.418806076049805,5138.9878340000005
+8568,Multiclass classification,Voting,Keystroke,0.8469709349830746,0.8469709349830746,0.8501227536717817,10.607142448425293,5616.664707000001
+8976,Multiclass classification,Voting,Keystroke,0.8475766016713092,0.8475766016713092,0.8507851780426926,10.772598266601562,6113.940894000001
+9384,Multiclass classification,Voting,Keystroke,0.8459980816370031,0.8459980816370031,0.8471668648040658,10.97368335723877,6631.342845000001
+9792,Multiclass classification,Voting,Keystroke,0.8418956184250843,0.8418956184250843,0.8426049398612477,11.192140579223633,7169.901201000001
+10200,Multiclass classification,Voting,Keystroke,0.8344935778017453,0.8344935778017454,0.8308153568434791,11.354521751403809,7729.92345
+10608,Multiclass classification,Voting,Keystroke,0.817384745922504,0.817384745922504,0.8105787344487394,11.59365177154541,8312.440227000001
+11016,Multiclass classification,Voting,Keystroke,0.8127099409895597,0.8127099409895597,0.8142119266109252,11.793928146362305,8918.030696000002
+11424,Multiclass classification,Voting,Keystroke,0.8079313665411888,0.8079313665411888,0.8037472320719128,11.945178031921387,9547.170938000001
+11832,Multiclass classification,Voting,Keystroke,0.8040740427689967,0.8040740427689967,0.8039730126613296,12.203582763671875,10200.281645000001
+12240,Multiclass classification,Voting,Keystroke,0.8072554947299616,0.8072554947299616,0.8097160881214022,12.414502143859863,10877.318664
+12648,Multiclass classification,Voting,Keystroke,0.8043014153554202,0.8043014153554202,0.8038043720799647,12.561456680297852,11578.515438
+13056,Multiclass classification,Voting,Keystroke,0.7996936039831483,0.7996936039831483,0.8010057260657798,12.889472007751465,12304.325005
+13464,Multiclass classification,Voting,Keystroke,0.7974448488449826,0.7974448488449826,0.7996515087686575,12.99599838256836,13054.609905000001
+13872,Multiclass classification,Voting,Keystroke,0.7978516329031793,0.7978516329031793,0.8006715750629478,13.20394229888916,13829.291085
+14280,Multiclass classification,Voting,Keystroke,0.797674907206387,0.7976749072063871,0.8002875748518964,13.364522933959961,14628.347686000001
+14688,Multiclass classification,Voting,Keystroke,0.8007761966364813,0.8007761966364813,0.8043248634763072,13.53370189666748,15451.756014
+15096,Multiclass classification,Voting,Keystroke,0.8051010268300762,0.8051010268300763,0.8085780284871096,13.774932861328125,16299.960754
+15504,Multiclass classification,Voting,Keystroke,0.8052634973876024,0.8052634973876024,0.8077470357827514,13.933537483215332,17172.988913
+15912,Multiclass classification,Voting,Keystroke,0.7978756834894098,0.7978756834894098,0.7983136026998061,14.138628005981445,18070.675966000003
+16320,Multiclass classification,Voting,Keystroke,0.793369691770329,0.7933696917703291,0.7956625263629296,14.30509090423584,18993.333450000002
+16728,Multiclass classification,Voting,Keystroke,0.7901596221677527,0.7901596221677527,0.7932579365729884,14.447582244873047,19941.842904
+17136,Multiclass classification,Voting,Keystroke,0.7861686606361249,0.7861686606361248,0.7888822346867281,14.767212867736816,20916.572711
+17544,Multiclass classification,Voting,Keystroke,0.780425240836801,0.780425240836801,0.7838193866310822,14.989240646362305,21922.215184
+17952,Multiclass classification,Voting,Keystroke,0.7802907915993538,0.7802907915993537,0.7845235361146662,15.200251579284668,22957.213951
+18360,Multiclass classification,Voting,Keystroke,0.783975162045863,0.783975162045863,0.7883700169311393,15.375930786132812,24020.765336
+18768,Multiclass classification,Voting,Keystroke,0.7869664837214259,0.7869664837214259,0.7913854757843782,15.5132417678833,25114.453204
+19176,Multiclass classification,Voting,Keystroke,0.7816427640156454,0.7816427640156454,0.7858184292134073,15.77665901184082,26236.293864000003
+19584,Multiclass classification,Voting,Keystroke,0.7846090997293571,0.7846090997293571,0.7893723685613512,15.996115684509277,27388.205854000003
+19992,Multiclass classification,Voting,Keystroke,0.7807013155920164,0.7807013155920164,0.785620728786203,16.12063980102539,28569.915626
+20400,Multiclass classification,Voting,Keystroke,0.7791068189617139,0.7791068189617139,0.7841355172773921,16.39253330230713,29779.243894000003
+46,Multiclass classification,[baseline] Last Class,ImageSegments,0.17777777777777778,0.17777777777777778,0.15260266049739735,0.0013666152954101562,0.110776
+92,Multiclass classification,[baseline] Last Class,ImageSegments,0.13186813186813187,0.13186813186813187,0.1213108980966124,0.0013637542724609375,0.225611
+138,Multiclass classification,[baseline] Last Class,ImageSegments,0.12408759124087591,0.12408759124087591,0.11874455065544491,0.001369476318359375,0.34363900000000003
+184,Multiclass classification,[baseline] Last Class,ImageSegments,0.12568306010928962,0.12568306010928962,0.12262983423071581,0.0013647079467773438,0.48452400000000007
+230,Multiclass classification,[baseline] Last Class,ImageSegments,0.12663755458515283,0.12663755458515283,0.12503852041208066,0.0013637542724609375,0.6292090000000001
+276,Multiclass classification,[baseline] Last Class,ImageSegments,0.12727272727272726,0.12727272727272726,0.12427907918144998,0.0013666152954101562,0.7861950000000001
+322,Multiclass classification,[baseline] Last Class,ImageSegments,0.13395638629283488,0.13395638629283488,0.13210036596246022,0.0013666152954101562,1.0166240000000002
+368,Multiclass classification,[baseline] Last Class,ImageSegments,0.13896457765667575,0.13896457765667575,0.13745011462972964,0.0013675689697265625,1.2507780000000002
+414,Multiclass classification,[baseline] Last Class,ImageSegments,0.14043583535108958,0.14043583535108958,0.14035813096947544,0.0013666152954101562,1.5223060000000002
+460,Multiclass classification,[baseline] Last Class,ImageSegments,0.14596949891067537,0.14596949891067537,0.14563148710727947,0.00136566162109375,1.7974560000000002
+506,Multiclass classification,[baseline] Last Class,ImageSegments,0.13861386138613863,0.13861386138613863,0.13833816102314941,0.0013666152954101562,2.0756200000000002
+552,Multiclass classification,[baseline] Last Class,ImageSegments,0.1397459165154265,0.1397459165154265,0.13938652491777898,0.0013666152954101562,2.402759
+598,Multiclass classification,[baseline] Last Class,ImageSegments,0.1373534338358459,0.1373534338358459,0.13727981043458612,0.0013675689697265625,2.771723
+644,Multiclass classification,[baseline] Last Class,ImageSegments,0.13996889580093314,0.13996889580093314,0.14017571709017965,0.0013666152954101562,3.149556
+690,Multiclass classification,[baseline] Last Class,ImageSegments,0.1378809869375907,0.1378809869375907,0.13801517784553327,0.001369476318359375,3.580436
+736,Multiclass classification,[baseline] Last Class,ImageSegments,0.1401360544217687,0.1401360544217687,0.14031088927958282,0.0013675689697265625,4.0152470000000005
+782,Multiclass classification,[baseline] Last Class,ImageSegments,0.14212548015364918,0.14212548015364918,0.1420930265541123,0.0013647079467773438,4.453992
+828,Multiclass classification,[baseline] Last Class,ImageSegments,0.14268440145102781,0.14268440145102781,0.14229874553046912,0.0013666152954101562,4.959761
+874,Multiclass classification,[baseline] Last Class,ImageSegments,0.13860252004581902,0.13860252004581902,0.13845352694595275,0.0013647079467773438,5.469480000000001
+920,Multiclass classification,[baseline] Last Class,ImageSegments,0.13492927094668117,0.13492927094668117,0.1348083913046733,0.0013666152954101562,6.0005820000000005
+966,Multiclass classification,[baseline] Last Class,ImageSegments,0.13367875647668392,0.13367875647668392,0.13349177774445276,0.0013637542724609375,6.5350530000000004
+1012,Multiclass classification,[baseline] Last Class,ImageSegments,0.13254203758654798,0.13254203758654798,0.1324936677659038,0.0013675689697265625,7.07275
+1058,Multiclass classification,[baseline] Last Class,ImageSegments,0.13339640491958374,0.13339640491958374,0.1331834965440007,0.00136566162109375,7.6454260000000005
+1104,Multiclass classification,[baseline] Last Class,ImageSegments,0.13417951042611062,0.13417951042611062,0.13402826529501538,0.0013666152954101562,8.221471000000001
+1150,Multiclass classification,[baseline] Last Class,ImageSegments,0.134029590948651,0.134029590948651,0.13406391150519123,0.0013637542724609375,8.800858000000002
+1196,Multiclass classification,[baseline] Last Class,ImageSegments,0.13640167364016736,0.13640167364016736,0.1363948420172951,0.001369476318359375,9.430169000000001
+1242,Multiclass classification,[baseline] Last Class,ImageSegments,0.13940370668815472,0.13940370668815472,0.13919772383892226,0.0013637542724609375,10.062783000000001
+1288,Multiclass classification,[baseline] Last Class,ImageSegments,0.1414141414141414,0.1414141414141414,0.14118715023210152,0.0013666152954101562,10.698372
+1334,Multiclass classification,[baseline] Last Class,ImageSegments,0.14328582145536384,0.14328582145536384,0.14302553278156666,0.0013637542724609375,11.387531000000001
+1380,Multiclass classification,[baseline] Last Class,ImageSegments,0.14358230601885424,0.14358230601885424,0.1433209000486506,0.001369476318359375,12.080639000000001
+1426,Multiclass classification,[baseline] Last Class,ImageSegments,0.14175438596491227,0.14175438596491227,0.14145466559291123,0.001369476318359375,12.777602000000002
+1472,Multiclass classification,[baseline] Last Class,ImageSegments,0.13936097892590074,0.13936097892590074,0.13907629713942624,0.0013647079467773438,13.546128000000001
+1518,Multiclass classification,[baseline] Last Class,ImageSegments,0.13974950560316415,0.13974950560316415,0.13951366685898453,0.0013666152954101562,14.318195000000001
+1564,Multiclass classification,[baseline] Last Class,ImageSegments,0.13691618682021753,0.13691618682021753,0.13664170474395118,0.0013666152954101562,15.093811
+1610,Multiclass classification,[baseline] Last Class,ImageSegments,0.13610938471100062,0.13610938471100062,0.13597683881903072,0.0013637542724609375,15.942934000000001
+1656,Multiclass classification,[baseline] Last Class,ImageSegments,0.1365558912386707,0.1365558912386707,0.13633224623774592,0.001369476318359375,16.795246000000002
+1702,Multiclass classification,[baseline] Last Class,ImageSegments,0.13932980599647266,0.13932980599647266,0.13901296274399097,0.0013675689697265625,17.650687
+1748,Multiclass classification,[baseline] Last Class,ImageSegments,0.14195764167143674,0.14195764167143674,0.14147197312723642,0.00136566162109375,18.510738
+1794,Multiclass classification,[baseline] Last Class,ImageSegments,0.14221974344673732,0.14221974344673732,0.14194103966110075,0.0013647079467773438,19.374685
+1840,Multiclass classification,[baseline] Last Class,ImageSegments,0.14138118542686243,0.14138118542686243,0.14114329766598663,0.0013675689697265625,20.242449999999998
+1886,Multiclass classification,[baseline] Last Class,ImageSegments,0.140053050397878,0.140053050397878,0.13973258713820755,0.0013666152954101562,21.182872999999997
+1932,Multiclass classification,[baseline] Last Class,ImageSegments,0.14293112377006734,0.14293112377006734,0.14275229229825853,0.0013666152954101562,22.126859999999997
+1978,Multiclass classification,[baseline] Last Class,ImageSegments,0.14618108244815378,0.14618108244815378,0.14597158151605963,0.001369476318359375,23.074112999999997
+2024,Multiclass classification,[baseline] Last Class,ImageSegments,0.14434008897676717,0.14434008897676717,0.14416625237761066,0.001369476318359375,24.067370999999998
+2070,Multiclass classification,[baseline] Last Class,ImageSegments,0.14403093281778637,0.14403093281778637,0.14385543497127623,0.0013666152954101562,25.063920999999997
+2116,Multiclass classification,[baseline] Last Class,ImageSegments,0.14468085106382977,0.14468085106382977,0.14460362317776573,0.0013637542724609375,26.063629999999996
+2162,Multiclass classification,[baseline] Last Class,ImageSegments,0.14530310041647385,0.14530310041647385,0.14520465913821792,0.001369476318359375,27.083891999999995
+2208,Multiclass classification,[baseline] Last Class,ImageSegments,0.14499320344358857,0.14499320344358857,0.14491109851991696,0.001369476318359375,28.107943999999996
+2254,Multiclass classification,[baseline] Last Class,ImageSegments,0.14647137150466044,0.14647137150466044,0.14640425534129609,0.0013666152954101562,29.207950999999998
+2300,Multiclass classification,[baseline] Last Class,ImageSegments,0.14789038712483688,0.14789038712483688,0.14788688524810298,0.0013675689697265625,30.311507
+2310,Multiclass classification,[baseline] Last Class,ImageSegments,0.14811606756171503,0.14811606756171503,0.14811566784252675,0.001369476318359375,31.415920999999997
+1056,Multiclass classification,[baseline] Last Class,Insects,0.15829383886255924,0.15829383886255924,0.1376212379233521,0.0013856887817382812,0.57267
+2112,Multiclass classification,[baseline] Last Class,Insects,0.16579819990525818,0.16579819990525818,0.15110451064118433,0.0013856887817382812,1.690872
+3168,Multiclass classification,[baseline] Last Class,Insects,0.17019261130407326,0.17019261130407326,0.15681512355039637,0.0013885498046875,3.2981429999999996
+4224,Multiclass classification,[baseline] Last Class,Insects,0.16599573762727918,0.16599573762727918,0.15254433156050665,0.0013856887817382812,5.4736839999999995
+5280,Multiclass classification,[baseline] Last Class,Insects,0.17086569426027656,0.17086569426027656,0.15676679113993588,0.0013837814331054688,8.202311
+6336,Multiclass classification,[baseline] Last Class,Insects,0.17379636937647988,0.17379636937647988,0.16137568195972998,0.0013837814331054688,11.448991
+7392,Multiclass classification,[baseline] Last Class,Insects,0.1752130970098769,0.1752130970098769,0.16189407904134778,0.0013837814331054688,15.242684
+8448,Multiclass classification,[baseline] Last Class,Insects,0.17722268260921037,0.17722268260921037,0.163740045170864,0.0013818740844726562,19.537217000000002
+9504,Multiclass classification,[baseline] Last Class,Insects,0.17731242765442493,0.17731242765442493,0.1637492974453096,0.0013885498046875,24.318802
+10560,Multiclass classification,[baseline] Last Class,Insects,0.17908892887584052,0.17908892887584052,0.16564210767474952,0.0013837814331054688,29.683683000000002
+11616,Multiclass classification,[baseline] Last Class,Insects,0.17899268187688333,0.17899268187688333,0.16559253835337612,0.0013856887817382812,35.598037000000005
+12672,Multiclass classification,[baseline] Last Class,Insects,0.18530502722752742,0.1853050272275274,0.18269809988409802,0.0013866424560546875,41.981502000000006
+13728,Multiclass classification,[baseline] Last Class,Insects,0.24797843665768193,0.24797843665768193,0.26603936845528803,0.0013866424560546875,48.94863000000001
+14784,Multiclass classification,[baseline] Last Class,Insects,0.2795778935263478,0.2795778935263478,0.28229742751715126,0.0013818740844726562,56.43945000000001
+15840,Multiclass classification,[baseline] Last Class,Insects,0.27615379758823155,0.27615379758823155,0.2847375853365436,0.0013818740844726562,64.48233200000001
+16896,Multiclass classification,[baseline] Last Class,Insects,0.2723290914471737,0.2723290914471737,0.2859139704285301,0.0013856887817382812,73.03679300000002
+17952,Multiclass classification,[baseline] Last Class,Insects,0.2720739791655061,0.2720739791655061,0.2880143206503878,0.0013866424560546875,82.10379000000002
+19008,Multiclass classification,[baseline] Last Class,Insects,0.28252748987215237,0.28252748987215237,0.2877504429321087,0.0013866424560546875,91.70347300000002
+20064,Multiclass classification,[baseline] Last Class,Insects,0.28724517769027563,0.28724517769027563,0.28667392366619265,0.0013818740844726562,101.81113500000002
+21120,Multiclass classification,[baseline] Last Class,Insects,0.28306264501160094,0.28306264501160094,0.28164766024255256,0.0013837814331054688,112.42818900000002
+22176,Multiclass classification,[baseline] Last Class,Insects,0.2805411499436302,0.2805411499436302,0.27862960725280095,0.0013866424560546875,123.55266000000002
+23232,Multiclass classification,[baseline] Last Class,Insects,0.2797124531875511,0.2797124531875511,0.27719419757933417,0.0013856887817382812,135.22034100000002
+24288,Multiclass classification,[baseline] Last Class,Insects,0.2777205912628155,0.2777205912628155,0.2745878480946635,0.0013866424560546875,147.32084400000002
+25344,Multiclass classification,[baseline] Last Class,Insects,0.2756579726157124,0.2756579726157124,0.27233803052028965,0.0013818740844726562,159.88729300000003
+26400,Multiclass classification,[baseline] Last Class,Insects,0.27394977082465244,0.27394977082465244,0.26996904425699914,0.0013837814331054688,172.95537600000003
+27456,Multiclass classification,[baseline] Last Class,Insects,0.27189947186304864,0.27189947186304864,0.26719485323886244,0.0013866424560546875,186.52082400000003
+28512,Multiclass classification,[baseline] Last Class,Insects,0.2723860965942969,0.2723860965942969,0.2686965366571337,0.0013885498046875,200.59564800000004
+29568,Multiclass classification,[baseline] Last Class,Insects,0.2738187844556431,0.2738187844556431,0.2720266804437783,0.0013885498046875,215.16150500000003
+30624,Multiclass classification,[baseline] Last Class,Insects,0.27538124938771513,0.27538124938771513,0.27486986638103517,0.0013885498046875,230.19075300000003
+31680,Multiclass classification,[baseline] Last Class,Insects,0.2780390795163989,0.2780390795163989,0.2784141751235631,0.0013856887817382812,245.71900300000004
+32736,Multiclass classification,[baseline] Last Class,Insects,0.279670077898274,0.279670077898274,0.28021922512452757,0.0013837814331054688,261.76959600000004
+33792,Multiclass classification,[baseline] Last Class,Insects,0.2808440117190968,0.2808440117190968,0.28119627453717067,0.0013856887817382812,278.22772000000003
+34848,Multiclass classification,[baseline] Last Class,Insects,0.2772405085086234,0.2772405085086234,0.27819051828647573,0.0013837814331054688,295.19763900000004
+35904,Multiclass classification,[baseline] Last Class,Insects,0.2739325404562293,0.2739325404562293,0.2754200456137155,0.0013856887817382812,312.64260700000005
+36960,Multiclass classification,[baseline] Last Class,Insects,0.271246516410076,0.271246516410076,0.27333283767820205,0.0013818740844726562,330.5037730000001
+38016,Multiclass classification,[baseline] Last Class,Insects,0.26855188741286334,0.26855188741286334,0.2710722002891223,0.0013856887817382812,348.8496650000001
+39072,Multiclass classification,[baseline] Last Class,Insects,0.277034117376059,0.277034117376059,0.2770619820799866,0.0013866424560546875,367.6207990000001
+40128,Multiclass classification,[baseline] Last Class,Insects,0.27617315024796274,0.27617315024796274,0.2760769006623072,0.0013837814331054688,386.8573710000001
+41184,Multiclass classification,[baseline] Last Class,Insects,0.27567200058276475,0.27567200058276475,0.27543526329721163,0.0013837814331054688,406.52795400000014
+42240,Multiclass classification,[baseline] Last Class,Insects,0.27401216884869434,0.27401216884869434,0.27359461935885426,0.0013885498046875,426.69962200000015
+43296,Multiclass classification,[baseline] Last Class,Insects,0.2738422450629403,0.2738422450629403,0.27319488690835786,0.0013856887817382812,447.37129900000014
+44352,Multiclass classification,[baseline] Last Class,Insects,0.2729588960790061,0.2729588960790061,0.27209116538690487,0.0013866424560546875,468.49129600000015
+45408,Multiclass classification,[baseline] Last Class,Insects,0.27205056489087587,0.27205056489087587,0.2708084959373003,0.0013866424560546875,490.06234300000017
+46464,Multiclass classification,[baseline] Last Class,Insects,0.27137722488862104,0.27137722488862104,0.2698631410415437,0.0013837814331054688,512.0778290000002
+47520,Multiclass classification,[baseline] Last Class,Insects,0.27235421620825356,0.27235421620825356,0.27170627983222856,0.0013837814331054688,534.5781510000002
+48576,Multiclass classification,[baseline] Last Class,Insects,0.2741327843540916,0.2741327843540916,0.27449463409742436,0.0013818740844726562,557.5265480000002
+49632,Multiclass classification,[baseline] Last Class,Insects,0.27535209848683284,0.27535209848683284,0.27650368764304034,0.0013818740844726562,580.9705880000001
+50688,Multiclass classification,[baseline] Last Class,Insects,0.2768362696549411,0.2768362696549411,0.27863440912734966,0.0013837814331054688,604.9012140000001
+51744,Multiclass classification,[baseline] Last Class,Insects,0.27827918752294994,0.27827918752294994,0.2805971515128955,0.0013885498046875,629.3033230000001
+52800,Multiclass classification,[baseline] Last Class,Insects,0.28911532415386654,0.28911532415386654,0.28929532027297566,0.0013866424560546875,654.1512880000001
+52848,Multiclass classification,[baseline] Last Class,Insects,0.2897610081934642,0.2897610081934642,0.28976272570313216,0.0013866424560546875,679.0036960000001
+408,Multiclass classification,[baseline] Last Class,Keystroke,0.9975429975429976,0.9975429975429976,0.9660408844388819,0.0006122589111328125,0.255536
+816,Multiclass classification,[baseline] Last Class,Keystroke,0.9975460122699387,0.9975460122699387,0.9879967903427672,0.0006628036499023438,0.794196
+1224,Multiclass classification,[baseline] Last Class,Keystroke,0.9975470155355682,0.9975470155355682,0.9931179599499375,0.000713348388671875,1.53447
+1632,Multiclass classification,[baseline] Last Class,Keystroke,0.9975475168608215,0.9975475168608215,0.9950750839342831,0.0012521743774414062,2.469131
+2040,Multiclass classification,[baseline] Last Class,Keystroke,0.9975478175576263,0.9975478175576263,0.9960150346160551,0.0013027191162109375,3.675833
+2448,Multiclass classification,[baseline] Last Class,Keystroke,0.9975480179812015,0.9975480179812015,0.9965317313935653,0.0013532638549804688,5.030286
+2856,Multiclass classification,[baseline] Last Class,Keystroke,0.9975481611208407,0.9975481611208407,0.9968424283169279,0.00140380859375,6.586031
+3264,Multiclass classification,[baseline] Last Class,Keystroke,0.9975482684646031,0.9975482684646031,0.9970416021996,0.0014543533325195312,8.377109
+3672,Multiclass classification,[baseline] Last Class,Keystroke,0.9975483519476982,0.9975483519476982,0.9971755428551425,0.0015048980712890625,10.331252000000001
+4080,Multiclass classification,[baseline] Last Class,Keystroke,0.9975484187300809,0.9975484187300809,0.9972690115789393,0.0015554428100585938,12.525489
+4488,Multiclass classification,[baseline] Last Class,Keystroke,0.9975484733675062,0.9975484733675062,0.9973361791525123,0.001605987548828125,14.940819000000001
+4896,Multiclass classification,[baseline] Last Class,Keystroke,0.9975485188968335,0.9975485188968335,0.9973856025730918,0.0016565322875976562,17.495259
+5304,Multiclass classification,[baseline] Last Class,Keystroke,0.9975485574203281,0.9975485574203281,0.9974226798335742,0.0017070770263671875,20.336762
+5712,Multiclass classification,[baseline] Last Class,Keystroke,0.9975485904395027,0.9975485904395027,0.99745094204078,0.0017576217651367188,23.402208
+6120,Multiclass classification,[baseline] Last Class,Keystroke,0.9975486190554013,0.9975486190554013,0.9974727709453766,0.00180816650390625,26.661861000000002
+6528,Multiclass classification,[baseline] Last Class,Keystroke,0.9975486440937643,0.9975486440937643,0.997489815700999,0.0018587112426757812,30.164710000000003
+6936,Multiclass classification,[baseline] Last Class,Keystroke,0.997548666186013,0.997548666186013,0.9975032443691146,0.0019092559814453125,33.838397
+7344,Multiclass classification,[baseline] Last Class,Keystroke,0.997548685823233,0.997548685823233,0.9975139007887865,0.0034246444702148438,37.738436
+7752,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487033931105,0.9975487033931105,0.9975224052755716,0.003475189208984375,41.800015
+8160,Multiclass classification,[baseline] Last Class,Keystroke,0.997548719205785,0.997548719205785,0.9975292209193424,0.0035257339477539062,46.105028000000004
+8568,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487335123147,0.9975487335123147,0.9975346982235258,0.0035762786865234375,50.63279300000001
+8976,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487465181059,0.9975487465181059,0.9975391057693664,0.0036268234252929688,55.447067000000004
+9384,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487583928381,0.9975487583928381,0.997542651662671,0.0036773681640625,60.387128000000004
+9792,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487692779083,0.9975487692779083,0.9975454987794795,0.0037279129028320312,65.547582
+10200,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487792920874,0.9975487792920874,0.9975477757646256,0.0037784576416015625,70.981052
+10608,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487885358726,0.9975487885358726,0.9975495850737114,0.0038290023803710938,76.594226
+11016,Multiclass classification,[baseline] Last Class,Keystroke,0.9975487970948707,0.9975487970948707,0.9975510089260562,0.003879547119140625,82.44596800000001
+11424,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488050424582,0.9975488050424582,0.9975521137613483,0.003930091857910156,88.533094
+11832,Multiclass classification,[baseline] Last Class,Keystroke,0.99754881244189,0.99754881244189,0.9975529536110199,0.0039806365966796875,94.81874400000001
+12240,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488193479859,0.9975488193479859,0.9975535726732964,0.004031181335449219,101.331754
+12648,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488258084921,0.9975488258084921,0.9975540072976319,0.00408172607421875,108.05167800000001
+13056,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488318651857,0.9975488318651857,0.997554287526727,0.004132270812988281,114.99668100000001
+13464,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488375547797,0.9975488375547797,0.9975544383040469,0.0041828155517578125,122.1119
+13872,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488429096676,0.9975488429096676,0.9975544804262362,0.004233360290527344,129.47010500000002
+14280,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488479585405,0.9975488479585405,0.9975544312994101,0.004283905029296875,136.988051
+14688,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488527269013,0.9975488527269013,0.9975543055435039,0.004334449768066406,144.742896
+15096,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488572374959,0.9975488572374959,0.9975541154780816,0.0043849945068359375,152.648866
+15504,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488615106753,0.9975488615106753,0.9975538715150367,0.004435539245605469,160.767465
+15912,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488655647037,0.9975488655647037,0.9975535824776959,0.004486083984375,169.09858
+16320,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488694160182,0.9975488694160182,0.9975532558614028,0.004536628723144531,177.653336
+16728,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488730794524,0.9975488730794524,0.997552898047314,0.0045871734619140625,186.438203
+17136,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488765684272,0.9975488765684272,0.9975525144785747,0.004637718200683594,195.44716799999998
+17544,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488798951149,0.9975488798951149,0.9975521098061079,0.004688262939453125,204.56363499999998
+17952,Multiclass classification,[baseline] Last Class,Keystroke,0.997548883070581,0.997548883070581,0.9975516880097278,0.004738807678222656,213.933058
+18360,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488861049077,0.9975488861049077,0.997551252499137,0.0047893524169921875,223.513668
+18768,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488890073001,0.9975488890073001,0.9975508061984416,0.004839897155761719,233.322943
+19176,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488917861799,0.9975488917861799,0.9975503516171184,0.00489044189453125,243.357771
+19584,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488944492672,0.9975488944492672,0.9975498909097889,0.004940986633300781,253.567103
+19992,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488970036517,0.9975488970036517,0.9975494259267257,0.0049915313720703125,264.004285
+20400,Multiclass classification,[baseline] Last Class,Keystroke,0.9975488994558557,0.9975488994558557,0.9975489582566448,0.005042076110839844,274.675054
diff --git a/docs/benchmarks/Regression/index.md b/docs/benchmarks/Regression/index.md
new file mode 100644
index 0000000000..ac378dd8ac
--- /dev/null
+++ b/docs/benchmarks/Regression/index.md
@@ -0,0 +1,20664 @@
+# Regression
+
+
+
+=== "Table"
+
+    | Model                                    | Dataset       |        MAE |       RMSE |            R2 |   Memory in Mb |   Time in s |
+    |:-----------------------------------------|:--------------|-----------:|-----------:|--------------:|---------------:|------------:|
+    | Adaptive Model Rules                     | ChickWeights  |  24.1943   |  37.2166   |    0.725319   |    0.046977    |    5.25855  |
+    | Adaptive Model Rules                     | TrumpApproval |   1.39847  |   2.43336  |   -1.02372    |    0.114429    |    9.38293  |
+    | Adaptive Random Forest                   | ChickWeights  |  26.1016   |  40.8094   |    0.669725   |    1.19043     |   56.006    |
+    | Adaptive Random Forest                   | TrumpApproval |   0.800378 |   2.11495  |   -0.528761   |    1.28462     |   87.4457   |
+    | Aggregated Mondrian Forest               | ChickWeights  |  25.6742   |  41.7123   |    0.65479    |    8.21412     |  127.415    |
+    | Aggregated Mondrian Forest               | TrumpApproval |   0.268533 |   0.349421 |    0.958184   |   16.9323      |  186.034    |
+    | Bagging                                  | ChickWeights  |  23.1143   |  36.6311   |    0.733893   |    0.628034    |   38.0203   |
+    | Bagging                                  | TrumpApproval |   0.908203 |   2.23718  |   -0.710572   |    1.31579     |   82.0689   |
+    | Exponentially Weighted Average           | ChickWeights  | 121.818    | 141.004    |   -2.94294    |    3.09241     |   55.8851   |
+    | Exponentially Weighted Average           | TrumpApproval |  40.7546   |  40.7905   | -567.663      |    5.27613     |  141.452    |
+    | Hoeffding Adaptive Tree                  | ChickWeights  |  23.3739   |  37.6579   |    0.718766   |    0.0947332   |    7.99029  |
+    | Hoeffding Adaptive Tree                  | TrumpApproval |   0.921313 |   2.23942  |   -0.713986   |    0.138225    |   16.7576   |
+    | Hoeffding Tree                           | ChickWeights  |  23.1619   |  36.7336   |    0.732402   |    0.0440512   |    6.29305  |
+    | Hoeffding Tree                           | TrumpApproval |   0.956103 |   2.24987  |   -0.730022   |    0.148639    |   11.7656   |
+    | Linear Regression                        | ChickWeights  |  23.7587   |  37.0377   |    0.727954   |    0.00421047  |    3.21471  |
+    | Linear Regression                        | TrumpApproval |   1.31455  |   3.91198  |   -4.23035    |    0.00497341  |   11.5379   |
+    | Linear Regression with l1 regularization | ChickWeights  |  23.7577   |  37.078    |    0.727361   |    0.00444126  |    9.7485   |
+    | Linear Regression with l1 regularization | TrumpApproval |   1.15377  |   3.82872  |   -4.01007    |    0.0052042   |   13.3595   |
+    | Linear Regression with l2 regularization | ChickWeights  |  25.2738   |  38.5885   |    0.704694   |    0.00423336  |    1.22128  |
+    | Linear Regression with l2 regularization | TrumpApproval |   1.87151  |   4.13052  |   -4.83107    |    0.0049963   |    4.15677  |
+    | Passive-Aggressive Regressor, mode 1     | ChickWeights  |  24.3423   |  37.596    |    0.71969    |    0.00345898  |    1.10187  |
+    | Passive-Aggressive Regressor, mode 1     | TrumpApproval |   4.98403  |   6.97667  |  -15.6354     |    0.00443554  |    2.99338  |
+    | Passive-Aggressive Regressor, mode 2     | ChickWeights  | 100.624    | 143.066    |   -3.05911    |    0.00345898  |    1.16798  |
+    | Passive-Aggressive Regressor, mode 2     | TrumpApproval |  31.0933   |  34.6257   | -408.765      |    0.00443554  |    4.72475  |
+    | River MLP                                | ChickWeights  |  51.4078   |  80.9203   |   -0.298584   |    0.0123129   |   28.2295   |
+    | River MLP                                | TrumpApproval |   1.58058  |   5.03392  |   -7.66066    |    0.0133505   |   32.2432   |
+    | Stochastic Gradient Tree                 | ChickWeights  |  68.7588   |  80.358    |   -0.280601   |    1.12059     |   22.3803   |
+    | Stochastic Gradient Tree                 | TrumpApproval |   9.42975  |  17.9379   | -108.972      |    3.08244     |   52.4507   |
+    | Streaming Random Patches                 | ChickWeights  |  23.7097   |  38.4416   |    0.706938   |    0.355182    |   93.4014   |
+    | Streaming Random Patches                 | TrumpApproval |   0.656697 |   1.98434  |   -0.345761   |    1.06461     |  134.903    |
+    | [baseline] Mean predictor                | ChickWeights  |  50.2509   |  71.1144   |   -0.00292947 |    0.000490189 |    0.302835 |
+    | [baseline] Mean predictor                | TrumpApproval |   1.56755  |   2.20286  |   -0.658483   |    0.000490189 |    1.08177  |
+    | k-Nearest Neighbors                      | ChickWeights  |  24.8406   |  39.2016   |    0.695236   |    2.88522     |   40.0878   |
+    | k-Nearest Neighbors                      | TrumpApproval |   0.641679 |   1.59417  |    0.131425   |    5.03263     |  123.301    |
+
+=== "Chart"
+
+    *Try reloading the page if something is buggy*
+
+    ```vegalite
+    {
+      "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
+      "data": {
+        "values": [
+          {
+            "step": 11,
+            "track": "Regression",
+            "model": "Linear Regression",
+            "dataset": "ChickWeights",
+            "MAE": 30.432219699626994,
+            "RMSE": 31.267456151778337,
+            "R2": -1257.4692714745631,
+            "Memory in Mb": 0.0041303634643554,
+            "Time in s": 0.000963
+          },
+          {
+            "step": 22,
+            "track": "Regression",
+            "model": "Linear Regression",
+            "dataset": "ChickWeights",
+            "MAE": 20.75760844034268,
+            "RMSE": 23.632210645041404,
+            "R2": -590.4769976066937,
+            "Memory in Mb": 0.0041303634643554,
+            "Time in s": 0.002374
+          },
+          {
+            "step": 33,
+            "track": "Regression",
+            "model": "Linear Regression",
+            "dataset": "ChickWeights",
+            "MAE": 14.555240079240876,
+            "RMSE": 19.34929493332969,
+            "R2": -259.0232069515881,
+            "Memory in Mb": 0.0041303634643554,
+            "Time in s": 0.004113
+          },
+          {
+            "step": 44,
+            "track": "Regression",
+            "model": "Linear Regression",
+            "dataset": "ChickWeights",
+            "MAE": 11.14363365913676,
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+          "color": {
+            "field": "model",
+            "type": "ordinal",
+            "scale": {
+              "scheme": "category20b"
+            },
+            "title": "Models",
+            "legend": {
+              "titleFontSize": 18,
+              "labelFontSize": 18,
+              "labelLimit": 500
+            }
+          },
+          "opacity": {
+            "condition": {
+              "param": "models",
+              "value": 1
+            },
+            "value": 0.2
+          }
+        }
+      }
+    }
+    ```
+
+            
+
+## Datasets
+
+???- abstract "ChickWeights"
+
+    Chick weights along time.
+
+    The stream contains 578 items and 3 features. The goal is to predict the weight of each chick
+    along time, according to the diet the chick is on. The data is ordered by time and then by
+    chick.
+
+        Name  ChickWeights                                                                                                  
+        Task  Regression                                                                                                    
+     Samples  578                                                                                                           
+    Features  3                                                                                                             
+      Sparse  False                                                                                                         
+        Path  /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/chick-weights.csv
+
+<span />
+
+???- abstract "TrumpApproval"
+
+    Donald Trump approval ratings.
+
+    This dataset was obtained by reshaping the data used by FiveThirtyEight for analyzing Donald
+    Trump's approval ratings. It contains 5 features, which are approval ratings collected by
+    5 polling agencies. The target is the approval rating from FiveThirtyEight's model. The goal of
+    this task is to see if we can reproduce FiveThirtyEight's model.
+
+        Name  TrumpApproval                                                                                                     
+        Task  Regression                                                                                                        
+     Samples  1,001                                                                                                             
+    Features  6                                                                                                                 
+      Sparse  False                                                                                                             
+        Path  /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/trump_approval.csv.gz
+
+<span />
+
+## Models
+
+???- example "Linear Regression"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      LinearRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=Squared ()
+        l2=0.
+        l1=0.
+        intercept_init=0.
+        intercept_lr=Constant (
+          learning_rate=0.01
+        )
+        clip_gradient=1e+12
+        initializer=Zeros ()
+      )
+    )</pre>
+
+<span />
+
+???- example "Linear Regression with l1 regularization"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      LinearRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=Squared ()
+        l2=0.
+        l1=1.
+        intercept_init=0.
+        intercept_lr=Constant (
+          learning_rate=0.01
+        )
+        clip_gradient=1e+12
+        initializer=Zeros ()
+      )
+    )</pre>
+
+<span />
+
+???- example "Linear Regression with l2 regularization"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      LinearRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=Squared ()
+        l2=1.
+        l1=0.
+        intercept_init=0.
+        intercept_lr=Constant (
+          learning_rate=0.01
+        )
+        clip_gradient=1e+12
+        initializer=Zeros ()
+      )
+    )</pre>
+
+<span />
+
+???- example "Passive-Aggressive Regressor, mode 1"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      PARegressor (
+        C=1.
+        mode=1
+        eps=0.1
+        learn_intercept=True
+      )
+    )</pre>
+
+<span />
+
+???- example "Passive-Aggressive Regressor, mode 2"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      PARegressor (
+        C=1.
+        mode=2
+        eps=0.1
+        learn_intercept=True
+      )
+    )</pre>
+
+<span />
+
+???- example "k-Nearest Neighbors"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      KNNRegressor (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        aggregation_method="mean"
+      )
+    )</pre>
+
+<span />
+
+???- example "Hoeffding Tree"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      HoeffdingTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+      )
+    )</pre>
+
+<span />
+
+???- example "Hoeffding Adaptive Tree"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=True
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=42
+      )
+    )</pre>
+
+<span />
+
+???- example "Stochastic Gradient Tree"
+
+    <pre>SGTRegressor (
+      delta=1e-07
+      grace_period=200
+      init_pred=0.
+      max_depth=inf
+      lambda_value=0.1
+      gamma=1.
+      nominal_attributes=[]
+      feature_quantizer=StaticQuantizer (
+        n_bins=64
+        warm_start=100
+        buckets=None
+      )
+    )</pre>
+
+<span />
+
+???- example "Adaptive Random Forest"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      []
+    )</pre>
+
+<span />
+
+???- example "Aggregated Mondrian Forest"
+
+    <pre>[]</pre>
+
+<span />
+
+???- example "Adaptive Model Rules"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      AMRules (
+        n_min=200
+        delta=1e-07
+        tau=0.05
+        pred_type="adaptive"
+        pred_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        fading_factor=0.99
+        anomaly_threshold=-0.75
+        m_min=30
+        ordered_rule_set=True
+        min_samples_split=5
+      )
+    )</pre>
+
+<span />
+
+???- example "Streaming Random Patches"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      SRPRegressor (
+        model=HoeffdingTreeRegressor (
+          grace_period=50
+          max_depth=inf
+          delta=0.01
+          tau=0.05
+          leaf_prediction="adaptive"
+          leaf_model=LinearRegression (
+            optimizer=SGD (
+              lr=Constant (
+                learning_rate=0.01
+              )
+            )
+            loss=Squared ()
+            l2=0.
+            l1=0.
+            intercept_init=0.
+            intercept_lr=Constant (
+              learning_rate=0.01
+            )
+            clip_gradient=1e+12
+            initializer=Zeros ()
+          )
+          model_selector_decay=0.95
+          nominal_attributes=None
+          splitter=TEBSTSplitter (
+            digits=1
+          )
+          min_samples_split=5
+          binary_split=False
+          max_size=500.
+          memory_estimate_period=1000000
+          stop_mem_management=False
+          remove_poor_attrs=False
+          merit_preprune=True
+        )
+        n_models=10
+        subspace_size=0.6
+        training_method="patches"
+        lam=6
+        drift_detector=ADWIN (
+          delta=1e-05
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        warning_detector=ADWIN (
+          delta=0.0001
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        disable_detector="off"
+        disable_weighted_vote=True
+        drift_detection_criteria="error"
+        aggregation_method="mean"
+        seed=42
+        metric=MAE ()
+      )
+    )</pre>
+
+<span />
+
+???- example "Bagging"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      [HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=False
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      )]
+    )</pre>
+
+<span />
+
+???- example "Exponentially Weighted Average"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      [LinearRegression (
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.01
+          )
+        )
+        loss=Squared ()
+        l2=0.
+        l1=0.
+        intercept_init=0.
+        intercept_lr=Constant (
+          learning_rate=0.01
+        )
+        clip_gradient=1e+12
+        initializer=Zeros ()
+      ), HoeffdingAdaptiveTreeRegressor (
+        grace_period=200
+        max_depth=inf
+        delta=1e-07
+        tau=0.05
+        leaf_prediction="adaptive"
+        leaf_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        model_selector_decay=0.95
+        nominal_attributes=None
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        min_samples_split=5
+        bootstrap_sampling=True
+        drift_window_threshold=300
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        switch_significance=0.05
+        binary_split=False
+        max_size=500.
+        memory_estimate_period=1000000
+        stop_mem_management=False
+        remove_poor_attrs=False
+        merit_preprune=True
+        seed=None
+      ), KNNRegressor (
+        n_neighbors=5
+        engine=SWINN (
+          graph_k=20
+          dist_func=FunctionWrapper (
+            distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)
+          )
+          maxlen=1000
+          warm_up=500
+          max_candidates=50
+          delta=0.0001
+          prune_prob=0.
+          n_iters=10
+          seed=None
+        )
+        aggregation_method="mean"
+      ), AMRules (
+        n_min=200
+        delta=1e-07
+        tau=0.05
+        pred_type="adaptive"
+        pred_model=LinearRegression (
+          optimizer=SGD (
+            lr=Constant (
+              learning_rate=0.01
+            )
+          )
+          loss=Squared ()
+          l2=0.
+          l1=0.
+          intercept_init=0.
+          intercept_lr=Constant (
+            learning_rate=0.01
+          )
+          clip_gradient=1e+12
+          initializer=Zeros ()
+        )
+        splitter=TEBSTSplitter (
+          digits=1
+        )
+        drift_detector=ADWIN (
+          delta=0.002
+          clock=32
+          max_buckets=5
+          min_window_length=5
+          grace_period=10
+        )
+        fading_factor=0.99
+        anomaly_threshold=-0.75
+        m_min=30
+        ordered_rule_set=True
+        min_samples_split=5
+      )]
+    )</pre>
+
+<span />
+
+???- example "River MLP"
+
+    <pre>Pipeline (
+      StandardScaler (
+        with_std=True
+      ),
+      MLPRegressor (
+        hidden_dims=(5,)
+        activations=(<class 'river.neural_net.activations.ReLU'>, <class 'river.neural_net.activations.ReLU'>, <class 'river.neural_net.activations.Identity'>)
+        loss=Squared ()
+        optimizer=SGD (
+          lr=Constant (
+            learning_rate=0.001
+          )
+        )
+        seed=42
+      )
+    )</pre>
+
+<span />
+
+???- example "[baseline] Mean predictor"
+
+    <pre>StatisticRegressor (
+      statistic=Mean ()
+    )</pre>
+
+<span />
+
+## Environment
+
+<pre>Python implementation: CPython
+Python version       : 3.10.13
+IPython version      : 8.16.1
+
+river       : 0.19.0
+numpy       : 1.25.2
+scikit-learn: 1.3.1
+pandas      : 2.1.1
+scipy       : 1.11.3
+
+Compiler    : Clang 14.0.6 
+OS          : Darwin
+Release     : 22.6.0
+Machine     : arm64
+Processor   : arm
+CPU cores   : 8
+Architecture: 64bit
+</pre>
+
diff --git a/docs/benchmarks/Regression/regression.csv b/docs/benchmarks/Regression/regression.csv
new file mode 100644
index 0000000000..6d0b88b0a6
--- /dev/null
+++ b/docs/benchmarks/Regression/regression.csv
@@ -0,0 +1,1769 @@
+step,track,model,dataset,MAE,RMSE,R2,Memory in Mb,Time in s
+11,Regression,Linear Regression,ChickWeights,30.432219699626994,31.267456151778337,-1257.4692714745631,0.004130363464355469,0.000963
+22,Regression,Linear Regression,ChickWeights,20.75760844034268,23.632210645041404,-590.4769976066937,0.004130363464355469,0.002374
+33,Regression,Linear Regression,ChickWeights,14.555240079240876,19.349294933329695,-259.0232069515881,0.004130363464355469,0.004113
+44,Regression,Linear Regression,ChickWeights,11.143633659136759,16.767243978820222,-220.34524244378574,0.004130363464355469,0.006175
+55,Regression,Linear Regression,ChickWeights,10.841164000616114,17.714902804136145,-60.2608923989398,0.004130363464355469,0.008581
+66,Regression,Linear Regression,ChickWeights,10.32598508406065,16.527353468164844,-21.985729074745297,0.004130363464355469,0.01133
+77,Regression,Linear Regression,ChickWeights,9.718401993814265,15.521096390186141,-12.587024696233003,0.004130363464355469,0.014424
+88,Regression,Linear Regression,ChickWeights,8.767755200283737,14.552446235427842,-9.829280875288257,0.004130363464355469,0.017858
+99,Regression,Linear Regression,ChickWeights,7.977130626229444,13.740429605807138,-7.074807888709797,0.004130363464355469,0.021634999999999998
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+429,Regression,Linear Regression,ChickWeights,15.109717404902197,24.642068489898374,0.7221580232945248,0.004210472106933594,1.4604629999999998
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+20,Regression,Linear Regression,TrumpApproval,20.715375599336316,24.276120972986362,-1381.3340079163324,0.004813194274902344,0.003774
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+860,Regression,Linear Regression,TrumpApproval,1.4815681878661566,4.217864876321593,-4.663732871777943,0.004973411560058594,6.863868000000001
+880,Regression,Linear Regression,TrumpApproval,1.4526831778170481,4.169823323470254,-4.507942651608292,0.004973411560058594,7.276079000000001
+900,Regression,Linear Regression,TrumpApproval,1.425504815240136,4.123417367951589,-4.4087270270070205,0.004973411560058594,7.880966000000001
+920,Regression,Linear Regression,TrumpApproval,1.401135420694234,4.078757160785335,-4.379153600942964,0.004973411560058594,8.488067000000001
+940,Regression,Linear Regression,TrumpApproval,1.3798894262867005,4.035722473386745,-4.310917809364017,0.004973411560058594,9.096757
+960,Regression,Linear Regression,TrumpApproval,1.3578157698337674,3.993911445090692,-4.255827563021541,0.004973411560058594,9.706153
+980,Regression,Linear Regression,TrumpApproval,1.3349554985290681,3.953168904153961,-4.2491478554421755,0.004973411560058594,10.316233
+1000,Regression,Linear Regression,TrumpApproval,1.3157385915327033,3.9139344489617316,-4.232086679588724,0.004973411560058594,10.926998000000001
+1001,Regression,Linear Regression,TrumpApproval,1.3145482000473083,3.9119809164882438,-4.230354806784151,0.004973411560058594,11.537908000000002
+11,Regression,Linear Regression with l1 regularization,ChickWeights,30.519429760441792,31.341724959881887,-1263.4547929656035,0.004361152648925781,0.001889
+22,Regression,Linear Regression with l1 regularization,ChickWeights,20.93274945698016,23.730069634788823,-595.3856524245364,0.004361152648925781,0.005264
+33,Regression,Linear Regression with l1 regularization,ChickWeights,14.671976905269485,19.432784890847977,-261.2719879213097,0.004361152648925781,0.045495999999999995
+44,Regression,Linear Regression with l1 regularization,ChickWeights,11.206218788565426,16.83704009498573,-222.1918420065333,0.004361152648925781,0.086209
+55,Regression,Linear Regression with l1 regularization,ChickWeights,10.7873677371092,17.69725945175844,-60.138926246201024,0.004361152648925781,0.127302
+66,Regression,Linear Regression with l1 regularization,ChickWeights,10.358479420064798,16.54420972880916,-22.032639310332936,0.004361152648925781,0.168766
+77,Regression,Linear Regression with l1 regularization,ChickWeights,9.753598876381378,15.536347024393615,-12.613738343052718,0.004361152648925781,0.21060099999999998
+88,Regression,Linear Regression with l1 regularization,ChickWeights,8.774706713989955,14.560860647391403,-9.841807755380493,0.004361152648925781,0.252804
+99,Regression,Linear Regression with l1 regularization,ChickWeights,7.976543403311107,13.74760854733656,-7.083247758311314,0.004361152648925781,0.295373
+110,Regression,Linear Regression with l1 regularization,ChickWeights,7.5284067705618165,13.110785837893241,-4.133835882207287,0.004361152648925781,0.338308
+121,Regression,Linear Regression with l1 regularization,ChickWeights,7.271666718491515,12.6229442838289,-2.665108536473531,0.004361152648925781,0.38161
+132,Regression,Linear Regression with l1 regularization,ChickWeights,6.91845605456336,12.134014714075713,-1.7679259750984961,0.004361152648925781,0.425278
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+154,Regression,Linear Regression with l1 regularization,ChickWeights,6.3485668448406924,11.31852948419668,-0.6578355548574832,0.004361152648925781,0.51371
+165,Regression,Linear Regression with l1 regularization,ChickWeights,6.473998962981321,11.222073845492618,-0.3100659276219817,0.004361152648925781,0.558476
+176,Regression,Linear Regression with l1 regularization,ChickWeights,6.543521830550948,11.096254270292283,-0.032756661210885385,0.004361152648925781,0.603607
+187,Regression,Linear Regression with l1 regularization,ChickWeights,6.493894355635018,10.908553918682982,0.18277886707380187,0.004361152648925781,0.649102
+198,Regression,Linear Regression with l1 regularization,ChickWeights,6.432058292739276,10.739983052449066,0.36987633376979445,0.004361152648925781,0.6949599999999999
+209,Regression,Linear Regression with l1 regularization,ChickWeights,6.530905166315106,10.805387069826965,0.47419925648761396,0.004361152648925781,0.74118
+220,Regression,Linear Regression with l1 regularization,ChickWeights,7.049069109840064,11.46222613381468,0.4819945238144716,0.004361152648925781,0.7877609999999999
+231,Regression,Linear Regression with l1 regularization,ChickWeights,7.185364391622807,11.520615160379734,0.5523912707049028,0.004361152648925781,0.834703
+242,Regression,Linear Regression with l1 regularization,ChickWeights,7.384443509591489,11.759466507882767,0.6247424700583044,0.004361152648925781,0.882006
+253,Regression,Linear Regression with l1 regularization,ChickWeights,7.370825288025247,11.706644644448966,0.6770052015955412,0.004361152648925781,0.929669
+264,Regression,Linear Regression with l1 regularization,ChickWeights,7.997212264968545,12.688148058774217,0.6533323093865229,0.004441261291503906,0.977694
+275,Regression,Linear Regression with l1 regularization,ChickWeights,8.45564901988644,13.583827871673952,0.6503637760490552,0.004441261291503906,1.026082
+286,Regression,Linear Regression with l1 regularization,ChickWeights,8.687395226209604,13.953064893865328,0.6804867014487179,0.004441261291503906,1.074833
+297,Regression,Linear Regression with l1 regularization,ChickWeights,8.660171229881424,13.910099225377925,0.7245931722706233,0.004441261291503906,1.1239519999999998
+308,Regression,Linear Regression with l1 regularization,ChickWeights,9.16625719191718,14.612234985526298,0.7293304097140514,0.004441261291503906,1.1734349999999998
+319,Regression,Linear Regression with l1 regularization,ChickWeights,10.250950211093048,17.0718306278326,0.664728869016383,0.004441261291503906,1.2232849999999997
+330,Regression,Linear Regression with l1 regularization,ChickWeights,10.679670450254022,17.65395670255975,0.6931807697512926,0.004441261291503906,1.3407639999999996
+341,Regression,Linear Regression with l1 regularization,ChickWeights,10.873729384474112,17.73873175202587,0.7226130148559202,0.004441261291503906,1.6983979999999996
+352,Regression,Linear Regression with l1 regularization,ChickWeights,11.018541118771262,17.831871437600412,0.745188204067577,0.004441261291503906,2.0571989999999998
+363,Regression,Linear Regression with l1 regularization,ChickWeights,11.899574150448762,19.190338217602402,0.7134289333715201,0.004441261291503906,2.417118
+374,Regression,Linear Regression with l1 regularization,ChickWeights,12.408282768986876,20.289550367060546,0.7055179762102581,0.004441261291503906,2.778154
+385,Regression,Linear Regression with l1 regularization,ChickWeights,12.788104615245373,20.897902847676004,0.7235998101431352,0.004441261291503906,3.1404569999999996
+396,Regression,Linear Regression with l1 regularization,ChickWeights,12.908222014164421,20.86950621812891,0.7429865604297317,0.004441261291503906,3.5031369999999997
+407,Regression,Linear Regression with l1 regularization,ChickWeights,13.785647364051679,22.333927174809716,0.726395986248676,0.004441261291503906,3.8661689999999997
+418,Regression,Linear Regression with l1 regularization,ChickWeights,14.562464823979756,23.771461386342615,0.709038397249883,0.004441261291503906,4.229544
+429,Regression,Linear Regression with l1 regularization,ChickWeights,15.115712915071189,24.692790084324347,0.7210130632693055,0.004441261291503906,4.59326
+440,Regression,Linear Regression with l1 regularization,ChickWeights,15.290646451171162,24.766775019882367,0.7392038606135755,0.004441261291503906,4.9573149999999995
+451,Regression,Linear Regression with l1 regularization,ChickWeights,15.806610158983217,25.370563596297366,0.7379667599208486,0.004441261291503906,5.321708999999999
+462,Regression,Linear Regression with l1 regularization,ChickWeights,16.91167446753811,27.489289014578034,0.711055524573946,0.004441261291503906,5.686440999999999
+473,Regression,Linear Regression with l1 regularization,ChickWeights,17.69453441784174,28.803034656505247,0.7198918720890418,0.004441261291503906,6.051508999999999
+484,Regression,Linear Regression with l1 regularization,ChickWeights,18.025914293879836,29.08166628667707,0.7300944167213836,0.004441261291503906,6.416912999999999
+495,Regression,Linear Regression with l1 regularization,ChickWeights,18.47687089345869,29.604201733284565,0.7368958634072684,0.004441261291503906,6.782651999999999
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+517,Regression,Linear Regression with l1 regularization,ChickWeights,20.096649322747314,32.051830787895724,0.717419357352562,0.004441261291503906,7.515149999999999
+528,Regression,Linear Regression with l1 regularization,ChickWeights,20.88685610593147,33.24610520798377,0.7266504806846955,0.004441261291503906,7.882236999999999
+539,Regression,Linear Regression with l1 regularization,ChickWeights,21.052957054073875,33.24035912136826,0.7380286507287471,0.004441261291503906,8.25334
+550,Regression,Linear Regression with l1 regularization,ChickWeights,22.046178761536364,34.86098206113683,0.7207414968982613,0.004441261291503906,8.62558
+561,Regression,Linear Regression with l1 regularization,ChickWeights,22.751953045975853,35.78242297978339,0.7186502822700677,0.004441261291503906,8.998921
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+578,Regression,Linear Regression with l1 regularization,ChickWeights,23.757667537133976,37.078025255419426,0.7273605875689941,0.004441261291503906,9.748496
+20,Regression,Linear Regression with l1 regularization,TrumpApproval,20.96628233331211,24.387937149248955,-1394.0974368768457,0.005043983459472656,0.003367
+40,Regression,Linear Regression with l1 regularization,TrumpApproval,12.95809265443779,17.886947111698607,-127.62867621055315,0.005043983459472656,0.060679000000000004
+60,Regression,Linear Regression with l1 regularization,TrumpApproval,10.43403375286247,15.198987179765494,-124.2101566950438,0.005043983459472656,0.118829
+80,Regression,Linear Regression with l1 regularization,TrumpApproval,8.76952679896777,13.348146279436204,-95.87145335263979,0.005043983459472656,0.177742
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+120,Regression,Linear Regression with l1 regularization,TrumpApproval,6.2853039116310185,10.94189036106609,-33.648027646243705,0.005043983459472656,0.297866
+140,Regression,Linear Regression with l1 regularization,TrumpApproval,5.5208355911538485,10.138862242229527,-29.74195117722151,0.005043983459472656,0.35901700000000003
+160,Regression,Linear Regression with l1 regularization,TrumpApproval,4.9080595636493145,9.487746704217276,-22.740310036230184,0.005043983459472656,0.420891
+180,Regression,Linear Regression with l1 regularization,TrumpApproval,4.437342628193194,8.948953859899,-17.549281500204398,0.005043983459472656,0.483487
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+400,Regression,Linear Regression with l1 regularization,TrumpApproval,2.263251524870982,6.020874949010495,-10.361708857360679,0.005204200744628906,2.4016
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+460,Regression,Linear Regression with l1 regularization,TrumpApproval,2.0360304025506277,5.61908468135586,-8.519416508014515,0.005204200744628906,3.319991
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+165,Regression,Linear Regression with l2 regularization,ChickWeights,8.136940986261356,11.920551719153746,-0.47822185831879493,0.004153251647949219,0.04749199999999999
+176,Regression,Linear Regression with l2 regularization,ChickWeights,8.284290032332207,11.93362687305613,-0.19451089204457617,0.004153251647949219,0.05348299999999999
+187,Regression,Linear Regression with l2 regularization,ChickWeights,8.390309464431912,11.903488345267945,0.026908395403585694,0.004153251647949219,0.05984699999999999
+198,Regression,Linear Regression with l2 regularization,ChickWeights,8.350219958465262,11.791481226840993,0.2404518209934976,0.004153251647949219,0.06659
+209,Regression,Linear Regression with l2 regularization,ChickWeights,8.499019855105985,11.958125495095471,0.3560283448388185,0.004153251647949219,0.073713
+220,Regression,Linear Regression with l2 regularization,ChickWeights,8.90272187978296,12.527163169679886,0.3812690011074207,0.004153251647949219,0.081218
+231,Regression,Linear Regression with l2 regularization,ChickWeights,9.171291167504231,12.73748746029564,0.45283948771259386,0.004153251647949219,0.08971
+242,Regression,Linear Regression with l2 regularization,ChickWeights,9.37629466014084,13.047657656056804,0.538024139715424,0.004153251647949219,0.099295
+253,Regression,Linear Regression with l2 regularization,ChickWeights,9.440817816219349,13.0964165059942,0.5957634168273553,0.004153251647949219,0.110134
+264,Regression,Linear Regression with l2 regularization,ChickWeights,9.906487060964153,13.855497684527965,0.5866088718530376,0.004233360290527344,0.12224199999999999
+275,Regression,Linear Regression with l2 regularization,ChickWeights,10.387009537918406,14.786939232799543,0.5856869069436603,0.004233360290527344,0.13552899999999998
+286,Regression,Linear Regression with l2 regularization,ChickWeights,10.701469010841246,15.270898285463774,0.6172820078624095,0.004233360290527344,0.14989199999999997
+297,Regression,Linear Regression with l2 regularization,ChickWeights,10.689852199892528,15.284847538688991,0.6674656839655615,0.004233360290527344,0.17720199999999997
+308,Regression,Linear Regression with l2 regularization,ChickWeights,11.168487287417783,16.008183102465477,0.6751444757196481,0.004233360290527344,0.20585199999999998
+319,Regression,Linear Regression with l2 regularization,ChickWeights,12.085867087734242,18.170753499240714,0.6201764868699093,0.004233360290527344,0.23488799999999999
+330,Regression,Linear Regression with l2 regularization,ChickWeights,12.672501856506585,19.05837058612535,0.6424226539377311,0.004233360290527344,0.26428199999999996
+341,Regression,Linear Regression with l2 regularization,ChickWeights,12.822446828447035,19.13937756684808,0.6770787925994421,0.004233360290527344,0.29402799999999996
+352,Regression,Linear Regression with l2 regularization,ChickWeights,13.055746883990931,19.312136445778254,0.7011272480618885,0.004233360290527344,0.32412699999999994
+363,Regression,Linear Regression with l2 regularization,ChickWeights,13.79008745873622,20.396105048894267,0.6762859401979866,0.004233360290527344,0.35457799999999995
+374,Regression,Linear Regression with l2 regularization,ChickWeights,14.293199062265238,21.539399675842862,0.6681199603719434,0.004233360290527344,0.38537999999999994
+385,Regression,Linear Regression with l2 regularization,ChickWeights,14.740320816630273,22.311026164960477,0.6849554171717112,0.004233360290527344,0.42616299999999996
+396,Regression,Linear Regression with l2 regularization,ChickWeights,14.862968645899144,22.294096988116678,0.7067005430463744,0.004233360290527344,0.467315
+407,Regression,Linear Regression with l2 regularization,ChickWeights,15.699705023283963,23.67314903355933,0.6925996644733732,0.004233360290527344,0.508826
+418,Regression,Linear Regression with l2 regularization,ChickWeights,16.38213993729544,25.048095107979137,0.6769473375050636,0.004233360290527344,0.55069
+429,Regression,Linear Regression with l2 regularization,ChickWeights,16.967894830794286,26.153201890569886,0.6870368010887093,0.004233360290527344,0.592905
+440,Regression,Linear Regression with l2 regularization,ChickWeights,17.10728249235129,26.204092785638924,0.7080553660644732,0.004233360290527344,0.6354690000000001
+451,Regression,Linear Regression with l2 regularization,ChickWeights,17.603016925007317,26.772391386711114,0.7082099437723521,0.004233360290527344,0.6783830000000001
+462,Regression,Linear Regression with l2 regularization,ChickWeights,18.614531201761594,28.786744962703725,0.6831362914484524,0.004233360290527344,0.7216460000000001
+473,Regression,Linear Regression with l2 regularization,ChickWeights,19.488293352005442,30.38515335394973,0.6882746780375071,0.004233360290527344,0.7652570000000001
+484,Regression,Linear Regression with l2 regularization,ChickWeights,19.755002868307955,30.52390276571354,0.7026599444855313,0.004233360290527344,0.8092140000000001
+495,Regression,Linear Regression with l2 regularization,ChickWeights,20.22217092676305,31.08727194033441,0.7098743070293987,0.004233360290527344,0.8535240000000001
+506,Regression,Linear Regression with l2 regularization,ChickWeights,21.03670858216615,32.44431034253017,0.6931769059461363,0.004233360290527344,0.898204
+517,Regression,Linear Regression with l2 regularization,ChickWeights,21.78200415465676,33.496021791915204,0.6913806254796178,0.004233360290527344,0.943264
+528,Regression,Linear Regression with l2 regularization,ChickWeights,22.56258004106143,34.768391171729405,0.7010449079513538,0.004233360290527344,0.9886969999999999
+539,Regression,Linear Regression with l2 regularization,ChickWeights,22.68725373887437,34.77075336357408,0.7133508993505916,0.004233360290527344,1.0345
+550,Regression,Linear Regression with l2 regularization,ChickWeights,23.627725892037507,36.324416048782524,0.6968033114915981,0.004233360290527344,1.080674
+561,Regression,Linear Regression with l2 regularization,ChickWeights,24.347376192466918,37.30920796407717,0.6941284720923248,0.004233360290527344,1.127216
+572,Regression,Linear Regression with l2 regularization,ChickWeights,25.18573737545828,38.51358935872805,0.698506895988072,0.004233360290527344,1.174127
+578,Regression,Linear Regression with l2 regularization,ChickWeights,25.27380465992389,38.58852748240754,0.7046942807227952,0.004233360290527344,1.2212839999999998
+20,Regression,Linear Regression with l2 regularization,TrumpApproval,20.994354275814885,24.339467027537435,-1388.5575385664913,0.004836082458496094,0.002841
+40,Regression,Linear Regression with l2 regularization,TrumpApproval,12.808927193108108,17.83271591943186,-126.84988353201342,0.004836082458496094,0.0066630000000000005
+60,Regression,Linear Regression with l2 regularization,TrumpApproval,10.864002308096953,15.320672400398038,-126.22308256175273,0.004836082458496094,0.011298
+80,Regression,Linear Regression with l2 regularization,TrumpApproval,8.882777304938948,13.38981065066765,-96.4771385394691,0.004836082458496094,0.01675
+100,Regression,Linear Regression with l2 regularization,TrumpApproval,7.231639558854497,11.98203471414171,-47.97617801736401,0.004836082458496094,0.023066000000000003
+120,Regression,Linear Regression with l2 regularization,TrumpApproval,6.334108393931037,10.98237795329033,-33.904913895880355,0.004836082458496094,0.030179000000000004
+140,Regression,Linear Regression with l2 regularization,TrumpApproval,5.563493982833803,10.178707085968126,-29.98405233271513,0.004836082458496094,0.038033000000000004
+160,Regression,Linear Regression with l2 regularization,TrumpApproval,5.002122045077101,9.533278572445496,-22.968717144675633,0.004836082458496094,0.04831800000000001
+180,Regression,Linear Regression with l2 regularization,TrumpApproval,4.587842803317817,9.003737317880292,-17.777085610739057,0.004836082458496094,0.07294600000000001
+200,Regression,Linear Regression with l2 regularization,TrumpApproval,4.458683971614509,8.652080760634158,-16.390543570087573,0.004836082458496094,0.09946700000000001
+220,Regression,Linear Regression with l2 regularization,TrumpApproval,4.239995800771734,8.280452519944822,-16.182419642449048,0.004836082458496094,0.129303
+240,Regression,Linear Regression with l2 regularization,TrumpApproval,3.943592784264584,7.932077353220182,-14.885669934585447,0.004836082458496094,0.159907
+260,Regression,Linear Regression with l2 regularization,TrumpApproval,3.7846302486799286,7.646201644169009,-13.960159512708739,0.004996299743652344,0.191262
+280,Regression,Linear Regression with l2 regularization,TrumpApproval,3.6468171672887713,7.389977926170562,-13.630953412847402,0.004996299743652344,0.22336299999999998
+300,Regression,Linear Regression with l2 regularization,TrumpApproval,3.5261123680869226,7.1621871014808685,-12.51535851099468,0.004996299743652344,0.25877399999999995
+320,Regression,Linear Regression with l2 regularization,TrumpApproval,3.5074300839639245,6.985469271455791,-12.493228210862723,0.004996299743652344,0.29652399999999995
+340,Regression,Linear Regression with l2 regularization,TrumpApproval,3.434140699763514,6.814822943627961,-12.570888751300782,0.004996299743652344,0.33652199999999993
+360,Regression,Linear Regression with l2 regularization,TrumpApproval,3.4272200155971797,6.678288393486038,-12.13957341395007,0.004996299743652344,0.3787709999999999
+380,Regression,Linear Regression with l2 regularization,TrumpApproval,3.332029752839207,6.516115548498917,-11.941900403072644,0.004996299743652344,0.4232519999999999
+400,Regression,Linear Regression with l2 regularization,TrumpApproval,3.217390968362987,6.356555790563252,-11.66392028459017,0.004996299743652344,0.4696459999999999
+420,Regression,Linear Regression with l2 regularization,TrumpApproval,3.100825681509746,6.206562691759863,-11.472880484909139,0.004996299743652344,0.516851
+440,Regression,Linear Regression with l2 regularization,TrumpApproval,3.0187726323631243,6.072312098448126,-10.723095644711893,0.004996299743652344,0.5652379999999999
+460,Regression,Linear Regression with l2 regularization,TrumpApproval,2.947022825868371,5.94849802587685,-9.668265577306911,0.004996299743652344,0.6161209999999999
+480,Regression,Linear Regression with l2 regularization,TrumpApproval,2.867282537241402,5.828292237410032,-9.005843404687633,0.004996299743652344,0.6743809999999999
+500,Regression,Linear Regression with l2 regularization,TrumpApproval,2.8281006485905213,5.729646774374514,-8.467133754251039,0.004996299743652344,0.7334769999999999
+520,Regression,Linear Regression with l2 regularization,TrumpApproval,2.759113137285707,5.623931694381955,-8.136932704030892,0.004996299743652344,0.79343
+540,Regression,Linear Regression with l2 regularization,TrumpApproval,2.7113951403332286,5.52770300084093,-7.7945843187225226,0.004996299743652344,0.8541829999999999
+560,Regression,Linear Regression with l2 regularization,TrumpApproval,2.646739535451309,5.4320905955210534,-7.695343452205655,0.004996299743652344,0.9420199999999999
+580,Regression,Linear Regression with l2 regularization,TrumpApproval,2.5972398336076634,5.343168086286508,-7.621065103502998,0.004996299743652344,1.0306859999999998
+600,Regression,Linear Regression with l2 regularization,TrumpApproval,2.533455116608919,5.255265792942869,-7.247487071141652,0.004996299743652344,1.1201999999999999
+620,Regression,Linear Regression with l2 regularization,TrumpApproval,2.497138699914293,5.178243230235351,-6.88544757519055,0.004996299743652344,1.2104949999999999
+640,Regression,Linear Regression with l2 regularization,TrumpApproval,2.4712145738198297,5.107804033669319,-6.528964961790648,0.004996299743652344,1.3015299999999999
+660,Regression,Linear Regression with l2 regularization,TrumpApproval,2.429247896498525,5.0347117637840935,-6.262430681498119,0.004996299743652344,1.3932969999999998
+680,Regression,Linear Regression with l2 regularization,TrumpApproval,2.3980901245026116,4.967521902410674,-6.18160824182094,0.004996299743652344,1.4857959999999997
+700,Regression,Linear Regression with l2 regularization,TrumpApproval,2.360396901712673,4.90286744871834,-6.1796262474179136,0.004996299743652344,1.5790619999999997
+720,Regression,Linear Regression with l2 regularization,TrumpApproval,2.3150393936015323,4.836721469702358,-6.140716883970916,0.004996299743652344,1.6730619999999998
+740,Regression,Linear Regression with l2 regularization,TrumpApproval,2.267679208737699,4.77254376860168,-5.948293801048677,0.004996299743652344,1.7677929999999997
+760,Regression,Linear Regression with l2 regularization,TrumpApproval,2.2434173929652075,4.715867112708654,-5.857742612566196,0.004996299743652344,1.8632789999999997
+780,Regression,Linear Regression with l2 regularization,TrumpApproval,2.199009654391343,4.656030786420359,-5.714767077599112,0.004996299743652344,1.9595409999999998
+800,Regression,Linear Regression with l2 regularization,TrumpApproval,2.1596596811720175,4.59898830049537,-5.610494506343661,0.004996299743652344,2.0566079999999998
+820,Regression,Linear Regression with l2 regularization,TrumpApproval,2.1249482408574707,4.545176313025559,-5.527610390446187,0.004996299743652344,2.175652
+840,Regression,Linear Regression with l2 regularization,TrumpApproval,2.094058354623314,4.493551443258636,-5.439404045425388,0.004996299743652344,2.37025
+860,Regression,Linear Regression with l2 regularization,TrumpApproval,2.062104039794744,4.442864622918497,-5.284107374622643,0.004996299743652344,2.565666
+880,Regression,Linear Regression with l2 regularization,TrumpApproval,2.0307065941401414,4.393695684791879,-5.115247638705276,0.004996299743652344,2.7618669999999996
+900,Regression,Linear Regression with l2 regularization,TrumpApproval,2.003263565299311,4.347049681772325,-5.011317673951863,0.004996299743652344,2.9588469999999996
+920,Regression,Linear Regression with l2 regularization,TrumpApproval,1.9706878923964866,4.300488305941944,-4.979898179552831,0.004996299743652344,3.1566579999999997
+940,Regression,Linear Regression with l2 regularization,TrumpApproval,1.949819924248383,4.257394252920471,-4.91037086709413,0.004996299743652344,3.355253
+960,Regression,Linear Regression with l2 regularization,TrumpApproval,1.9258186229947107,4.214725843085415,-4.85305905428677,0.004996299743652344,3.5546249999999997
+980,Regression,Linear Regression with l2 regularization,TrumpApproval,1.9004260103609922,4.173138113177231,-4.849565137575967,0.004996299743652344,3.754774
+1000,Regression,Linear Regression with l2 regularization,TrumpApproval,1.872733130377695,4.13253797119814,-4.832859832721421,0.004996299743652344,3.955698
+1001,Regression,Linear Regression with l2 regularization,TrumpApproval,1.871510887330926,4.130524228438989,-4.8310671605777085,0.004996299743652344,4.156775
+11,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,26.624124996337724,28.77138517975663,-1064.5628215382144,0.0034055709838867188,0.000572
+22,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,16.0510878175865,20.931739283093208,-463.02330712701985,0.0034055709838867188,0.001645
+33,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,12.49930786476168,17.564629142555763,-213.26922094451623,0.0034055709838867188,0.003059
+44,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,10.378514545021682,15.405121473747096,-185.84310618709696,0.0034055709838867188,0.004809
+55,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,10.844108697295251,17.128215293517524,-56.27037115396167,0.0034055709838867188,0.0068920000000000006
+66,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,9.889488781892217,15.88743125142584,-20.240220516271876,0.0034055709838867188,0.009306
+77,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,9.103343480706034,14.91594241381016,-11.548186613409534,0.0034055709838867188,0.012052
+88,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,8.288900850158633,14.011374344891147,-9.038968322803399,0.0034055709838867188,0.015129
+99,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.736865157066078,13.281093172283262,-6.5439573170464564,0.0034055709838867188,0.018712
+110,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.618125386224052,12.858171267844924,-3.9379074608874927,0.0034055709838867188,0.022717
+121,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.580936033253089,12.515247629942861,-2.6028352541815996,0.0034055709838867188,0.027127000000000002
+132,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.191573127926202,12.024287681643044,-1.7180920054032294,0.0034055709838867188,0.031928
+143,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.001452140019149,11.63905100750295,-1.062756769701151,0.0034055709838867188,0.037113999999999994
+154,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,6.959260067984971,11.397763679955697,-0.6811278108981134,0.0034055709838867188,0.04268899999999999
+165,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.036161429677985,11.359538570018055,-0.3423577921849861,0.0034055709838867188,0.04865399999999999
+176,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.141200516910354,11.407680550849575,-0.09154063283497149,0.0034055709838867188,0.05501099999999999
+187,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.061965626679777,11.211626858308708,0.1367382583661435,0.0034055709838867188,0.06175399999999999
+198,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,6.988600359846859,11.023879576943443,0.33612315722527375,0.0034055709838867188,0.06888499999999999
+209,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.115468527113427,11.18859440458875,0.43624345152336885,0.0034055709838867188,0.07639599999999999
+220,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.571784360381598,11.998798941058181,0.4323613497222297,0.0034055709838867188,0.08428799999999999
+231,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.610536559977233,11.962244483436113,0.5174164020157423,0.0034055709838867188,0.09375399999999999
+242,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.753677752144043,12.109970858596688,0.6020391290764042,0.0034055709838867188,0.10451099999999999
+253,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,7.763402728464486,12.046916639776326,0.6579556132088519,0.0034055709838867188,0.123112
+264,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,8.37232599699494,12.938281421109101,0.6395292100633578,0.0034589767456054688,0.147917
+275,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,8.870502401884236,14.03783628218945,0.6266016212673495,0.0034589767456054688,0.173118
+286,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,9.125553299295866,14.312481045438886,0.6638140497188074,0.0034589767456054688,0.198688
+297,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,9.11642729851449,14.234872044017683,0.7115826499817814,0.0034589767456054688,0.225283
+308,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,9.63053955101658,15.01159987060024,0.7143329631149452,0.0034589767456054688,0.252265
+319,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,10.671899739762464,17.42953249336733,0.650531972004655,0.0034589767456054688,0.27961600000000003
+330,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,11.113559839827301,17.980470366868552,0.6817264420663893,0.0034589767456054688,0.307329
+341,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,11.368994570730054,18.183536514460908,0.7085274545262112,0.0034589767456054688,0.335405
+352,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,11.47998520043724,18.216810890558104,0.7340681346165732,0.0034589767456054688,0.363842
+363,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,12.490995837872445,19.84181186896939,0.693641639088806,0.0034589767456054688,0.392636
+374,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,12.988870134156189,20.81926805033374,0.6899406322869175,0.0034589767456054688,0.42178699999999997
+385,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,13.420579982415202,21.48960215237335,0.7077263415053474,0.0034589767456054688,0.45129199999999997
+396,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,13.424816444492956,21.37796604773129,0.7303103668220552,0.0034589767456054688,0.481151
+407,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,14.284688005634004,22.701575115822557,0.7173140296578691,0.0034589767456054688,0.514769
+418,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,15.038658536726118,24.042516108283174,0.7023651722582169,0.0034589767456054688,0.548784
+429,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,15.590290098257741,24.916858152232297,0.7159269075042054,0.0034589767456054688,0.583167
+440,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,15.812702077031824,25.072500493300815,0.7327254930224041,0.0034589767456054688,0.617914
+451,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,16.346042839206106,25.68091484988461,0.7315167856134144,0.0034589767456054688,0.653021
+462,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,17.370765923434053,27.689388199834635,0.7068336630361484,0.0034589767456054688,0.688487
+473,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,18.264179516209435,29.30099868065636,0.7101227966068765,0.0034589767456054688,0.724309
+484,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,18.63502154656571,29.559619400414906,0.7211497930314269,0.0034589767456054688,0.760485
+495,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,19.145243718121584,30.130361606680754,0.7274603750306702,0.0034589767456054688,0.7970149999999999
+506,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,19.98075812634153,31.43770898148617,0.7119202509985216,0.0034589767456054688,0.8338999999999999
+517,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,20.7046141289421,32.42665929478992,0.7107714616434232,0.0034589767456054688,0.8711439999999999
+528,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,21.54126059149082,33.75343345950398,0.7182443212146572,0.0034589767456054688,0.908739
+539,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,21.736037457517718,33.829762552174344,0.7286559632490104,0.0034589767456054688,0.946687
+550,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,22.674609740448528,35.33904665998618,0.7130297805712756,0.0034589767456054688,0.984985
+561,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,23.350956760305525,36.24046007710213,0.7114012814424304,0.0034589767456054688,1.023633
+572,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,24.20743030595361,37.47019278346573,0.7146215025224946,0.0034589767456054688,1.06263
+578,Regression,"Passive-Aggressive Regressor, mode 1",ChickWeights,24.342328163686027,37.59599019491026,0.7196900586014492,0.0034589767456054688,1.1018649999999999
+20,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,20.806898309502586,26.56763494383828,-1654.6182189603317,0.004302024841308594,0.003003
+40,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,14.866074912822512,20.957300378156614,-175.5777711351631,0.004302024841308594,0.009504
+60,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,11.772648582583251,17.555009093750932,-166.03688377592212,0.004302024841308594,0.016813
+80,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,10.372925375947808,15.758572852966298,-134.01675577859288,0.004302024841308594,0.024890000000000002
+100,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,9.950999863257042,14.807263848606526,-73.79513907078027,0.004302024841308594,0.033777
+120,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,9.131163180965077,13.743973626529105,-53.66614209724606,0.004302024841308594,0.043434
+140,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,8.532294463666167,12.935885124148239,-49.04322437944699,0.004302024841308594,0.05944
+160,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,8.33219708929472,12.40854626547306,-39.60710527883104,0.004302024841308594,0.077842
+180,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,8.281092452540433,12.043698542516514,-32.597139849683785,0.004302024841308594,0.09862299999999999
+200,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,7.889313429527772,11.548268653424005,-29.981738551789036,0.004302024841308594,0.121857
+220,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,7.555718436766954,11.115454500430198,-29.962115725262894,0.004302024841308594,0.149384
+240,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,7.300584612865839,10.768588372618428,-28.278525817685868,0.004302024841308594,0.177703
+260,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,7.073956995660685,10.455941089275187,-26.975057358486694,0.004435539245605469,0.206834
+280,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,6.879100927439736,10.179149173565092,-26.75935065850941,0.004435539245605469,0.236782
+300,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,6.698392466938299,9.935855831167725,-25.01038668400382,0.004435539245605469,0.26759
+320,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,6.496977203333427,9.674599820332077,-24.881575653507443,0.004435539245605469,0.299212
+340,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,6.319501534649956,9.433800456219284,-25.005937123592886,0.004435539245605469,0.33164299999999997
+360,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,6.189316591643737,9.224778235838508,-24.070488458586468,0.004435539245605469,0.36488499999999996
+380,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,6.05373584315195,9.026036673488779,-23.83217081250324,0.004435539245605469,0.39894499999999994
+400,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.893196935767096,8.831009888188627,-23.44247524737401,0.004435539245605469,0.43386499999999995
+420,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.787168115685009,8.669033337133486,-23.33356914323267,0.004435539245605469,0.46960899999999994
+440,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.789860410241021,8.633597516354541,-22.69832962851382,0.004435539245605469,0.5061589999999999
+460,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.751464501173282,8.532971696368575,-20.952287666855003,0.004435539245605469,0.5516559999999999
+480,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.758413491181221,8.476961067588123,-20.166616413985547,0.004435539245605469,0.599555
+500,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.682950272504451,8.3510488559106,-19.111518541810455,0.004435539245605469,0.6519079999999999
+520,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.627995468360723,8.245754355787446,-18.64179334000355,0.004435539245605469,0.705132
+540,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.546541731300828,8.130789587119862,-18.02792190581397,0.004435539245605469,0.7591289999999999
+560,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.474658569482086,8.019262742277965,-17.95054121046633,0.004435539245605469,0.813877
+580,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.409420416004319,7.920158789530457,-17.94222667017848,0.004435539245605469,0.869386
+600,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.394854582323811,7.870548110777217,-17.498743363524373,0.004435539245605469,0.941553
+620,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.360408122735632,7.801849933723111,-16.900148820132806,0.004435539245605469,1.016153
+640,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.332182524169608,7.745335706289596,-16.312002846243146,0.004435539245605469,1.093294
+660,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.286484086266954,7.672164501241343,-15.864310422998045,0.004435539245605469,1.1728
+680,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.240017672508232,7.591734569529257,-15.773518040276521,0.004435539245605469,1.259908
+700,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.203631741702394,7.526058935068808,-15.917522479350382,0.004435539245605469,1.347915
+720,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.1985518333986755,7.481861117849272,-16.086729414362967,0.004435539245605469,1.436748
+740,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.200051628353664,7.4433149034441595,-15.900950117878587,0.004435539245605469,1.526395
+760,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.146415466772512,7.367313347205083,-15.736951087672441,0.004435539245605469,1.61685
+780,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.164438314106662,7.352756459959702,-15.745558187055657,0.004435539245605469,1.708114
+800,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.199091748701669,7.381485816300255,-16.029304780133675,0.004435539245605469,1.8001699999999998
+820,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.184244405270293,7.343677512392477,-16.040406471643664,0.004435539245605469,1.892982
+840,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.162940711797175,7.2951968772545595,-15.972283354719572,0.004435539245605469,1.986541
+860,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.146772746928229,7.251973114148485,-15.742866229030533,0.004435539245605469,2.080851
+880,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.141562534384022,7.225910341165371,-15.54014218136778,0.004435539245605469,2.175912
+900,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.113671043317916,7.181653170625269,-15.40700562565575,0.004435539245605469,2.271722
+920,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.0827257569327715,7.134180367835326,-15.456838882747107,0.004435539245605469,2.368328
+940,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.049460198345376,7.092641752853287,-15.403746251323405,0.004435539245605469,2.491683
+960,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,5.012955702794688,7.041188655025779,-15.335641983730405,0.004435539245605469,2.616037
+980,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,4.992587411597517,7.002009756347646,-15.468099715303381,0.004435539245605469,2.7412199999999998
+1000,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,4.986581819477306,6.97972894589718,-15.638912943338369,0.004435539245605469,2.867218
+1001,Regression,"Passive-Aggressive Regressor, mode 1",TrumpApproval,4.984033991902679,6.9766666383395455,-15.63541499061877,0.004435539245605469,2.993378
+11,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,39.19936706045659,55.118879370280126,-3909.733983269086,0.0034055709838867188,0.001533
+22,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,31.495026158423794,43.23165104261441,-1978.3965328342838,0.0034055709838867188,0.004589
+33,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,30.680053698816124,39.985066603327745,-1109.3949268723327,0.0034055709838867188,0.008788
+44,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,29.375885022911746,37.29886968855784,-1094.3128086885838,0.0034055709838867188,0.014141
+55,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,31.707444751978134,40.753235251415205,-323.21264874535376,0.0034055709838867188,0.020635
+66,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,31.96097441162184,40.14945868859866,-134.64726490280094,0.0034055709838867188,0.028271
+77,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,32.25989567011213,39.82501544894248,-88.45229320906665,0.0034055709838867188,0.041195
+88,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,32.76307262878121,39.802536485586,-80.01195436020778,0.0034055709838867188,0.054526000000000005
+99,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,32.66411513705659,39.325402336106926,-65.1420916497486,0.0034055709838867188,0.06822700000000001
+110,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,34.19940912800194,40.704130728492046,-48.48362457590105,0.0034055709838867188,0.082293
+121,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,34.629161705635866,40.92880988729008,-37.532194399087835,0.0034055709838867188,0.096719
+132,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,35.29035427006805,41.59178542812187,-31.520750879588867,0.0034055709838867188,0.111503
+143,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,36.23638449140802,42.62018794050648,-26.659453761649477,0.0034055709838867188,0.126644
+154,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,36.725010132899186,42.91835139661213,-22.836775105518452,0.0034055709838867188,0.14214100000000002
+165,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,36.731745662210095,42.91744223234227,-18.16084111691443,0.0034055709838867188,0.15799600000000003
+176,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,37.94402632003076,44.39720610255875,-15.533183531813599,0.0034055709838867188,0.17420800000000003
+187,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,38.698580833397834,45.06856008203835,-12.949305609255877,0.0034055709838867188,0.19077600000000003
+198,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,40.18624064352699,46.68267333461602,-10.905017439998023,0.0034055709838867188,0.20770000000000002
+209,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,40.854323276826534,47.463811090322665,-9.145320047375163,0.0034055709838867188,0.224978
+220,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,41.36451127701117,48.41262940233051,-8.240888884363313,0.0034055709838867188,0.24261000000000002
+231,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,42.17342712408468,49.46918668675267,-7.253093192412523,0.0034055709838867188,0.260594
+242,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,43.81461612103895,51.73551020684679,-6.2632609796369465,0.0034055709838867188,0.27893
+253,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,44.90819615603068,53.07334253773936,-5.6387075541588505,0.0034055709838867188,0.297618
+264,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,46.45334973048907,55.82244674340302,-5.710187070138379,0.0034589767456054688,0.31665899999999997
+275,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,48.05643802527038,58.804796990371536,-5.552357606253864,0.0034589767456054688,0.33605399999999996
+286,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,49.41721923566732,60.72765972830183,-5.052332799264802,0.0034589767456054688,0.35580199999999995
+297,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,51.23299901747073,63.29154255446438,-4.701716347098143,0.0034589767456054688,0.37590499999999993
+308,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,52.82583967659276,65.36972550348784,-4.417008197806662,0.0034589767456054688,0.39636799999999994
+319,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,54.851023886215806,70.45860717413167,-4.71089374971376,0.0034589767456054688,0.41718399999999994
+330,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,56.58220488738844,72.62689780553444,-4.192702597603254,0.0034589767456054688,0.43835299999999994
+341,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,58.456862484765374,75.26810540469758,-3.994165343488624,0.0034589767456054688,0.45987999999999996
+352,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,59.98229295122657,76.97767263775137,-3.748486775975887,0.0034589767456054688,0.48176199999999997
+363,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,61.989108820835376,80.62951920841103,-4.0588898392459045,0.0034589767456054688,0.503996
+374,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,63.93796840595574,84.48840832488506,-4.106322034628877,0.0034589767456054688,0.526584
+385,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,65.15236861414519,85.79755918852514,-3.6588935912158114,0.0034589767456054688,0.551564
+396,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,66.90365663892747,87.9249329113371,-3.562003118430529,0.0034589767456054688,0.5777180000000001
+407,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,68.17917622540308,89.58756462611774,-3.402382103640547,0.0034589767456054688,0.6050150000000001
+418,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,70.80702754948452,94.96753809429286,-3.643808228470034,0.0034589767456054688,0.6334650000000001
+429,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,72.44730173566225,97.09455233033468,-3.313534410167211,0.0034589767456054688,0.663057
+440,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,74.29167351363806,99.40774027870643,-3.2014833153265316,0.0034589767456054688,0.693783
+451,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,75.83174494284101,101.77506329990584,-3.216760347648722,0.0034589767456054688,0.725638
+462,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,78.5111288104629,106.99570126481906,-3.3774383617967887,0.0034589767456054688,0.758621
+473,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,81.63741116996734,112.58139375423264,-3.2793958269429844,0.0034589767456054688,0.79391
+484,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,82.66628549198501,113.50934761838603,-3.1118432523868984,0.0034589767456054688,0.829617
+495,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,84.40016304476833,116.34990208847,-3.0639935553557365,0.0034589767456054688,0.865723
+506,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,86.52132256561038,120.30772815943004,-3.2188880650982723,0.0034589767456054688,0.902224
+517,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,87.79244029751037,121.63869088166206,-3.0698668478095374,0.0034589767456054688,0.9391200000000001
+528,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,90.43735682351402,126.62066541565774,-2.9650251625135784,0.0034589767456054688,0.9763980000000001
+539,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,91.59763342322412,127.62959496409519,-2.862114672867245,0.0034589767456054688,1.014034
+550,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,93.80067010965053,131.39026699356185,-2.9669210878459156,0.0034589767456054688,1.0520230000000002
+561,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,96.52355815418714,136.33091173427522,-3.0840934586689466,0.0034589767456054688,1.0903630000000002
+572,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,99.60515399822415,141.80943605664237,-3.0875177525301325,0.0034589767456054688,1.1290550000000001
+578,Regression,"Passive-Aggressive Regressor, mode 2",ChickWeights,100.62422612381133,143.06646930774232,-3.0591132110693486,0.0034589767456054688,1.167982
+20,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,48.24517612267716,65.52170729560882,-10068.892101934754,0.004302024841308594,0.0014
+40,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,41.96170708962665,54.398737007050464,-1188.7151382109587,0.004302024841308594,0.0037089999999999996
+60,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,37.75687919715097,48.78450375470138,-1288.953469480389,0.004302024841308594,0.0068
+80,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,34.906129137913965,44.99379649673769,-1099.675197364534,0.004302024841308594,0.010662
+100,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,33.91700787894482,42.88559259598606,-626.4029768570122,0.004302024841308594,0.015342999999999999
+120,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,33.25318798467783,41.41783833748641,-495.44216046034904,0.004302024841308594,0.020797999999999997
+140,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,32.454169303664,40.065346416262614,-479.0547686921885,0.004302024841308594,0.027020999999999996
+160,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.456143135335843,38.757475924320815,-395.16052146995384,0.004302024841308594,0.034013999999999996
+180,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.609503890456164,37.605439707525925,-326.55474603918685,0.004302024841308594,0.04177499999999999
+200,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.18524212396377,36.915721425331306,-315.5882175367347,0.004302024841308594,0.05032999999999999
+220,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.065472528043387,36.44442035805252,-331.8421153382835,0.004302024841308594,0.05964399999999999
+240,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.78865598017145,35.91292614465666,-324.6366197799479,0.004302024841308594,0.06971499999999999
+260,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.781114432924582,35.79236523689611,-326.81251307944893,0.004435539245605469,0.08530999999999998
+280,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.533238425747374,35.35890478021234,-333.95306350592915,0.004435539245605469,0.10330299999999998
+300,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.457831453745214,35.09485674586195,-323.50634592736793,0.004435539245605469,0.12379499999999997
+320,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.587592426740265,34.99099947403571,-337.56135797788454,0.004435539245605469,0.14665799999999998
+340,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.592186767063264,34.82748458593961,-353.4405109424598,0.004435539245605469,0.178415
+360,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.811871336212132,34.87255971663822,-357.27671195740294,0.004435539245605469,0.21101599999999998
+380,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,29.96085998978186,34.8837386376585,-369.9082961036221,0.004435539245605469,0.24444299999999997
+400,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.10861760053803,34.89146879370085,-380.5600928496674,0.004435539245605469,0.27875099999999997
+420,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.237056214581205,34.87113676993804,-392.72834237954817,0.004435539245605469,0.31389799999999995
+440,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.396870134836657,34.919939008119975,-386.68686883790514,0.004435539245605469,0.34987699999999994
+460,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.514209015244397,34.936230377424984,-366.98596965456716,0.004435539245605469,0.38662699999999994
+480,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.60304766371323,34.90556469597589,-357.88920799289923,0.004435539245605469,0.42413599999999996
+500,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.723498435612367,34.929338036322235,-350.83863344189655,0.004435539245605469,0.462404
+520,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.811640107301315,34.91688659850233,-351.20164208687333,0.004435539245605469,0.5014689999999999
+540,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.90684609870959,34.93305250730057,-350.23597283973027,0.004435539245605469,0.541291
+560,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.83222834631613,34.80844611918478,-356.0442181025925,0.004435539245605469,0.58187
+580,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.81214247339674,34.7464796172207,-363.5733105101423,0.004435539245605469,0.629234
+600,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.96266506693229,34.82326914665847,-361.13570824853826,0.004435539245605469,0.6774979999999999
+620,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.066025409450507,34.86865150113252,-356.54586556020155,0.004435539245605469,0.743837
+640,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.17687176552783,34.929241693507976,-351.0830657253844,0.004435539245605469,0.810979
+660,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.17965741293356,34.892251240403844,-347.8114699445998,0.004435539245605469,0.87889
+680,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.2564554130016,34.924087575336145,-353.970503405387,0.004435539245605469,0.947564
+700,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.205643809070587,34.8991435368638,-362.77351000506667,0.004435539245605469,1.017054
+720,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.176512353694502,34.84497410939031,-369.61240318757564,0.004435539245605469,1.087302
+740,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.10578554229227,34.74995813099662,-367.37224871607793,0.004435539245605469,1.158309
+760,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.047274834607858,34.691812272848594,-370.11801689051305,0.004435539245605469,1.23401
+780,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.10380007346799,34.703384372728905,-372.0292841604823,0.004435539245605469,1.319073
+800,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.08555480002386,34.670374973731704,-374.68721566223496,0.004435539245605469,1.406663
+820,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.19885148971359,34.750222550469864,-380.56447731408525,0.004435539245605469,1.496625
+840,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.254637155655836,34.7657556157579,-384.4513633760299,0.004435539245605469,1.5889890000000002
+860,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.316317159155098,34.79186578621207,-384.3655387384781,0.004435539245605469,1.693075
+880,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.241979864666273,34.706915019978055,-380.5804591262153,0.004435539245605469,2.065505
+900,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.224226006229813,34.673719949901624,-381.45588348920205,0.004435539245605469,2.440347
+920,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.14134426690263,34.58836614994504,-385.8283921715467,0.004435539245605469,2.817664
+940,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.997921544748234,34.45657797481166,-386.1428842704396,0.004435539245605469,3.197344
+960,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.060400411885407,34.566740304864304,-392.69608794190344,0.004435539245605469,3.57811
+980,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,30.96911325529305,34.515642414657464,-399.1566023636026,0.004435539245605469,3.959721
+1000,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.09609109084082,34.63142513356851,-408.62698817771025,0.004435539245605469,4.342153
+1001,Regression,"Passive-Aggressive Regressor, mode 2",TrumpApproval,31.093334457100017,34.62570772928248,-408.7651443035993,0.004435539245605469,4.724752
+11,Regression,k-Nearest Neighbors,ChickWeights,4.6439393939393945,12.708027567111456,-206.8805289598106,0.0208587646484375,0.001745
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+77,Regression,k-Nearest Neighbors,ChickWeights,2.6114718614718617,5.706903555891601,-0.8368793810695487,0.0782623291015625,0.06880900000000001
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+297,Regression,k-Nearest Neighbors,ChickWeights,9.403647586980924,14.487230370517851,0.7012657763253116,0.27368927001953125,3.1592620000000005
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+143,Regression,Bagging,ChickWeights,4.439022558662509,6.895745596080793,0.2759386934515202,0.5216274261474609,1.284562
+154,Regression,Bagging,ChickWeights,4.362170284876481,6.736533340066285,0.4127346685162743,0.5262050628662109,1.543379
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+198,Regression,Bagging,ChickWeights,4.887061675652274,7.15502256260352,0.720333392468735,0.3514680862426758,2.944156
+209,Regression,Bagging,ChickWeights,5.070260383978678,7.484020932149266,0.7477619935177958,0.3277406692504883,3.412471
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+253,Regression,Bagging,ChickWeights,6.19844823305091,9.33633324769997,0.7945607849348244,0.42070865631103516,5.506109
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+20,Regression,Bagging,TrumpApproval,6.57361785669815,13.877675781396096,-450.73930630825186,0.3875865936279297,0.030628
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+60,Regression,Bagging,TrumpApproval,3.120546196671925,8.124382016407804,-34.775930157070896,0.6946392059326172,0.180013
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+44,Regression,Exponentially Weighted Average,ChickWeights,41.159090909090914,41.174517715340755,-1333.7620984139928,0.10875988006591797,0.065964
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+66,Regression,Exponentially Weighted Average,ChickWeights,42.681818181818166,42.82080349691271,-153.29834830483878,0.1604146957397461,0.17057299999999997
+77,Regression,Exponentially Weighted Average,ChickWeights,43.506493506493506,43.70978671356627,-106.75487995129542,0.18252849578857422,0.23188899999999998
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+121,Regression,Exponentially Weighted Average,ChickWeights,47.21487603305785,47.67304278378361,-51.27707184490422,0.23778057098388672,0.583103
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+143,Regression,Exponentially Weighted Average,ChickWeights,49.44055944055945,50.100318941519305,-37.220279564063546,0.22072410583496094,1.018133
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+198,Regression,Exponentially Weighted Average,ChickWeights,56.02525252525252,57.635786091488654,-17.146924852486976,0.30018043518066406,2.3857599999999994
+209,Regression,Exponentially Weighted Average,ChickWeights,57.5645933014354,59.46206220864915,-14.922837840066967,0.27625083923339844,2.7086299999999994
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+308,Regression,Exponentially Weighted Average,ChickWeights,72.39285714285718,77.65033596401675,-6.643510181414674,0.3809375762939453,7.597348
+319,Regression,Exponentially Weighted Average,ChickWeights,73.45454545454551,79.15086186624424,-6.206879640065647,0.39273643493652344,8.345726
+330,Regression,Exponentially Weighted Average,ChickWeights,75.77878787878792,82.20832738177494,-5.653192449779911,0.40398597717285156,9.225203
+341,Regression,Exponentially Weighted Average,ChickWeights,77.92375366568919,84.89106353805269,-5.352795814687307,0.4136791229248047,10.124705
+352,Regression,Exponentially Weighted Average,ChickWeights,80.04545454545458,87.49376601169416,-5.134510311668016,0.4233722686767578,11.048248000000001
+363,Regression,Exponentially Weighted Average,ChickWeights,80.99724517906337,88.57562798692558,-5.105139086016474,0.43306541442871094,11.989622
+374,Regression,Exponentially Weighted Average,ChickWeights,82.77807486631018,90.83029071422122,-4.901675845817959,0.45247840881347656,12.967698
+385,Regression,Exponentially Weighted Average,ChickWeights,85.1766233766234,93.99517810235533,-4.591702735915359,0.4681224822998047,14.032748
+396,Regression,Exponentially Weighted Average,ChickWeights,87.26767676767678,96.48964983485283,-4.494054297851511,0.48465919494628906,15.12168
+407,Regression,Exponentially Weighted Average,ChickWeights,89.00737100737103,98.71879502607636,-4.345544683073043,0.4991130828857422,16.236767999999998
+418,Regression,Exponentially Weighted Average,ChickWeights,90.57416267942587,100.72635724110245,-4.224084264201084,0.5109386444091797,17.416859999999996
+429,Regression,Exponentially Weighted Average,ChickWeights,93.12121212121215,104.19735398794236,-3.9677178403495805,0.5206584930419922,18.643557999999995
+440,Regression,Exponentially Weighted Average,ChickWeights,95.41818181818185,107.03565676064125,-3.8710119659250104,0.5303516387939453,19.910713999999995
+451,Regression,Exponentially Weighted Average,ChickWeights,97.16629711751665,109.07665280092142,-3.843505105397095,0.5280742645263672,21.225085999999994
+462,Regression,Exponentially Weighted Average,ChickWeights,98.71645021645023,111.17636431671961,-3.72620239405422,0.5443019866943359,22.607732999999993
+473,Regression,Exponentially Weighted Average,ChickWeights,101.54122621564484,115.20584573786859,-3.4812404756668593,0.5577869415283203,24.015635999999994
+484,Regression,Exponentially Weighted Average,ChickWeights,103.77066115702482,117.90601559037043,-3.4365483842712585,0.5712184906005859,25.474227999999993
+495,Regression,Exponentially Weighted Average,ChickWeights,106.02424242424244,120.71525892518193,-3.37467008920777,0.5825443267822266,26.96779499999999
+506,Regression,Exponentially Weighted Average,ChickWeights,107.31620553359684,122.26004165941237,-3.356924458603192,2.7805843353271484,30.43480299999999
+517,Regression,Exponentially Weighted Average,ChickWeights,109.39651837524178,124.91233289427785,-3.291877964737682,2.825040817260742,33.93932499999999
+528,Regression,Exponentially Weighted Average,ChickWeights,112.36553030303028,129.1106745698386,-3.1225038051323804,2.876035690307617,37.48648499999999
+539,Regression,Exponentially Weighted Average,ChickWeights,114.52504638218922,131.65752925403248,-3.109734667916423,2.927671432495117,41.07985699999999
+550,Regression,Exponentially Weighted Average,ChickWeights,115.89999999999996,133.35909826820617,-3.0866973064470367,2.9773387908935547,44.71417799999999
+561,Regression,Exponentially Weighted Average,ChickWeights,117.86452762923346,135.8046463151548,-3.0526234314410727,3.0208263397216797,48.39640499999999
+572,Regression,Exponentially Weighted Average,ChickWeights,120.54020979020974,139.4624607986965,-2.953338846956928,3.065652847290039,52.120071999999986
+578,Regression,Exponentially Weighted Average,ChickWeights,121.81833910034597,141.00422703423635,-2.942935834251463,3.092409133911133,55.885136999999986
+20,Regression,Exponentially Weighted Average,TrumpApproval,43.8732195,43.87807788634269,-4514.954899312423,0.1445150375366211,0.017697
+40,Regression,Exponentially Weighted Average,TrumpApproval,42.4932955,42.522552834216924,-725.9491167623446,0.21173763275146484,0.059669
+60,Regression,Exponentially Weighted Average,TrumpApproval,42.2167785,42.2386240157387,-966.0073736019044,0.25832653045654297,0.116093
+80,Regression,Exponentially Weighted Average,TrumpApproval,41.975705625,41.997608685598294,-957.9655948743646,0.3003568649291992,0.19454100000000002
+100,Regression,Exponentially Weighted Average,TrumpApproval,41.37550450000001,41.410913785433536,-583.9966399141301,0.3407926559448242,0.29552300000000004
+120,Regression,Exponentially Weighted Average,TrumpApproval,40.936110000000006,40.978293821977665,-484.9611418859003,0.3709287643432617,0.510712
+140,Regression,Exponentially Weighted Average,TrumpApproval,40.6885472857143,40.72961738075088,-495.1050461477588,0.3974485397338867,0.760252
+160,Regression,Exponentially Weighted Average,TrumpApproval,40.35105437500001,40.39801158334292,-429.4078677932073,0.3402233123779297,1.044132
+180,Regression,Exponentially Weighted Average,TrumpApproval,40.00981655555555,40.06373388340122,-370.7794659133543,0.3811016082763672,1.367502
+200,Regression,Exponentially Weighted Average,TrumpApproval,39.806330949999996,39.860362966711,-368.1089073295326,0.3127880096435547,1.794637
+220,Regression,Exponentially Weighted Average,TrumpApproval,39.727043136363626,39.77723500009918,-395.50198072931875,0.3578624725341797,2.266575
+240,Regression,Exponentially Weighted Average,TrumpApproval,39.56323079166665,39.61325406766278,-395.19837684116754,0.3875255584716797,2.775551
+260,Regression,Exponentially Weighted Average,TrumpApproval,39.42014538461535,39.46968290441584,-397.63185900832246,0.42084693908691406,3.358614
+280,Regression,Exponentially Weighted Average,TrumpApproval,39.33200189285712,39.37942345737111,-414.45601593500356,0.47014808654785156,4.097303
+300,Regression,Exponentially Weighted Average,TrumpApproval,39.18435719999999,39.23275803924839,-404.5402138221895,0.5117359161376953,4.882924
+320,Regression,Exponentially Weighted Average,TrumpApproval,39.13568690624999,39.1818628962716,-423.5167725219512,0.5480670928955078,5.740529
+340,Regression,Exponentially Weighted Average,TrumpApproval,39.14620944117645,39.18989510023786,-447.7943063391533,0.5615406036376953,6.72918
+360,Regression,Exponentially Weighted Average,TrumpApproval,39.24072974999997,39.28395553300239,-453.6543473793619,0.5990085601806641,7.76074
+380,Regression,Exponentially Weighted Average,TrumpApproval,39.29597665789471,39.337699215460226,-470.6701690846498,0.6312580108642578,8.924786000000001
+400,Regression,Exponentially Weighted Average,TrumpApproval,39.35730624999997,39.39781946688104,-485.4842825426507,0.6682605743408203,10.154856
+420,Regression,Exponentially Weighted Average,TrumpApproval,39.40549083333331,39.44465897881697,-502.77995042269276,0.6983966827392578,11.469727
+440,Regression,Exponentially Weighted Average,TrumpApproval,39.49730674999998,39.53710368662846,-495.9856416828035,0.7316226959228516,12.901862000000001
+460,Regression,Exponentially Weighted Average,TrumpApproval,39.61474728260867,39.65658853240579,-473.14358309219216,0.7705020904541016,14.448849000000001
+480,Regression,Exponentially Weighted Average,TrumpApproval,39.71032456249997,39.753047582709755,-464.4916761787406,0.8079357147216797,16.094285
+500,Regression,Exponentially Weighted Average,TrumpApproval,39.80313951999997,39.84667590965187,-456.87508245086684,2.9298267364501953,19.825027
+520,Regression,Exponentially Weighted Average,TrumpApproval,39.873547134615364,39.916931033645376,-459.2932847271911,3.0076160430908203,23.629967
+540,Regression,Exponentially Weighted Average,TrumpApproval,39.94649651851849,39.98996046818772,-459.28610565666287,3.1059207916259766,27.509295
+560,Regression,Exponentially Weighted Average,TrumpApproval,39.976066142857114,40.018487723609816,-470.92618770667195,3.203706741333008,31.453258
+580,Regression,Exponentially Weighted Average,TrumpApproval,40.00338510344825,40.044755101652726,-483.2331705341176,3.296670913696289,35.460995000000004
+600,Regression,Exponentially Weighted Average,TrumpApproval,40.07393431666663,40.11569326301364,-479.5746686678817,3.391347885131836,39.544454
+620,Regression,Exponentially Weighted Average,TrumpApproval,40.1459417741935,40.18827077358568,-473.96334667177865,3.4906063079833984,43.697410000000005
+640,Regression,Exponentially Weighted Average,TrumpApproval,40.219438156249964,40.26249426545423,-466.8085709746123,3.5870800018310547,47.924640000000004
+660,Regression,Exponentially Weighted Average,TrumpApproval,40.28296777272724,40.32626722721455,-464.9172853497744,3.6864986419677734,52.218165000000006
+680,Regression,Exponentially Weighted Average,TrumpApproval,40.31998279411761,40.36256991107017,-473.1325264408024,3.782560348510742,56.58359200000001
+700,Regression,Exponentially Weighted Average,TrumpApproval,40.31359012857138,40.35509446667054,-485.40526703956544,3.816682815551758,61.02307200000001
+720,Regression,Exponentially Weighted Average,TrumpApproval,40.31730695833329,40.357915759594896,-496.1610725544049,3.917215347290039,65.52718500000002
+740,Regression,Exponentially Weighted Average,TrumpApproval,40.36653568918915,40.407119416424955,-497.07428037101636,4.021100997924805,70.10250300000001
+760,Regression,Exponentially Weighted Average,TrumpApproval,40.403143671052604,40.443256311482514,-503.3712175162706,4.113973617553711,74.743136
+780,Regression,Exponentially Weighted Average,TrumpApproval,40.44545064102563,40.48534274444009,-506.6856716110208,4.221334457397461,79.45160200000001
+800,Regression,Exponentially Weighted Average,TrumpApproval,40.478548249999996,40.518050685964006,-512.1052117095793,4.33137321472168,84.22367000000001
+820,Regression,Exponentially Weighted Average,TrumpApproval,40.50894034146341,40.5479845946661,-518.5068774177179,4.393171310424805,89.06994900000001
+840,Regression,Exponentially Weighted Average,TrumpApproval,40.5406558690476,40.579310897365986,-524.140575335229,4.501546859741211,93.98653900000001
+860,Regression,Exponentially Weighted Average,TrumpApproval,40.58371181395347,40.62239247493601,-524.3496319016275,4.600507736206055,98.97766000000001
+880,Regression,Exponentially Weighted Average,TrumpApproval,40.62855514772725,40.66738601007716,-522.897851512946,4.697576522827148,104.03937600000002
+900,Regression,Exponentially Weighted Average,TrumpApproval,40.664104233333326,40.702738445808535,-526.020768835918,4.774164199829102,109.17863200000002
+920,Regression,Exponentially Weighted Average,TrumpApproval,40.68274704347825,40.72073961991632,-535.1540147256861,4.872934341430664,114.38942200000002
+940,Regression,Exponentially Weighted Average,TrumpApproval,40.70972619148935,40.74737437775791,-540.4099749760601,4.975519180297852,119.67171900000002
+960,Regression,Exponentially Weighted Average,TrumpApproval,40.734006364583315,40.771242977826994,-546.7118652484228,5.07771110534668,125.02115000000002
+980,Regression,Exponentially Weighted Average,TrumpApproval,40.74031829795916,40.776840159239676,-557.5026042066913,5.174932479858398,130.44017000000002
+1000,Regression,Exponentially Weighted Average,TrumpApproval,40.75359492299998,40.78950075300399,-567.2567645513548,5.274145126342773,135.92720000000003
+1001,Regression,Exponentially Weighted Average,TrumpApproval,40.75458054545452,40.7904615623717,-567.6629514867817,5.276128768920898,141.45243100000002
+11,Regression,River MLP,ChickWeights,41.63636363636363,41.64569169030137,-2231.5319148936137,0.012152671813964844,0.004659
+22,Regression,River MLP,ChickWeights,41.31818181818181,41.32960638133835,-1808.0547045951903,0.012152671813964844,0.035685
+33,Regression,River MLP,ChickWeights,41.12121212121212,41.13871582091424,-1174.393494897962,0.012152671813964844,0.08499899999999999
+44,Regression,River MLP,ChickWeights,41.159090909090914,41.174517715340755,-1333.7620984139928,0.012152671813964844,0.154054
+55,Regression,River MLP,ChickWeights,41.5090909090909,41.57075020645253,-336.3506066081568,0.012152671813964844,0.236038
+66,Regression,River MLP,ChickWeights,42.681818181818166,42.82080349691271,-153.29834830483878,0.012152671813964844,0.334153
+77,Regression,River MLP,ChickWeights,43.46421300395698,43.662828265715675,-106.52347713504811,0.012152671813964844,0.44537099999999996
+88,Regression,River MLP,ChickWeights,43.359772412267546,43.583709810639945,-96.13505707304522,0.012152671813964844,0.810611
+99,Regression,River MLP,ChickWeights,39.34760833403674,41.28110871337288,-71.88434940071843,0.012152671813964844,1.1795
+110,Regression,River MLP,ChickWeights,36.27694842893514,39.43109665219568,-45.43679588251114,0.012152671813964844,1.5519370000000001
+121,Regression,River MLP,ChickWeights,33.384495302116036,37.629851771248454,-31.570957412576163,0.012152671813964844,1.9276810000000002
+132,Regression,River MLP,ChickWeights,30.760956861305427,36.03410144813446,-23.410283906032372,0.012152671813964844,2.306782
+143,Regression,River MLP,ChickWeights,28.636527077105512,34.63559483719005,-17.266619380249022,0.012152671813964844,2.6893580000000004
+154,Regression,River MLP,ChickWeights,26.848366395937333,33.39569685051843,-13.432529594168455,0.012152671813964844,3.0876050000000004
+165,Regression,River MLP,ChickWeights,25.68994399106157,32.40192925941153,-9.921659843170621,0.012152671813964844,3.5625080000000002
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+187,Regression,River MLP,ChickWeights,23.27797268834062,30.533192270092133,-5.402500905628177,0.012152671813964844,4.523515000000001
+198,Regression,River MLP,ChickWeights,22.21718064008457,29.702466677215767,-3.8195183008370286,0.012152671813964844,5.01074
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+220,Regression,River MLP,ChickWeights,21.477175147376318,28.875533005215566,-2.287429329651187,0.012152671813964844,6.006767
+231,Regression,River MLP,ChickWeights,20.952511346795177,28.337840419816686,-1.7081998467380504,0.012152671813964844,6.546588
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+286,Regression,River MLP,ChickWeights,20.565278129073285,27.847512109279503,-0.27268965368266684,0.012312889099121094,9.312993
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+319,Regression,River MLP,ChickWeights,21.510251079645446,30.009813508826145,-0.03600670421086383,0.012312889099121094,11.038549000000001
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+40,Regression,River MLP,TrumpApproval,17.631407237579232,23.536801219235826,-221.7205207554288,0.013110160827636719,0.053933999999999996
+60,Regression,River MLP,TrumpApproval,13.441671937224772,19.739075566761823,-210.18539534147195,0.013110160827636719,0.098078
+80,Regression,River MLP,TrumpApproval,11.196749290061339,17.292913087737123,-161.5886474703317,0.013110160827636719,0.159515
+100,Regression,River MLP,TrumpApproval,9.529407951935296,15.54264880746251,-81.40884208187767,0.013110160827636719,0.228076
+120,Regression,River MLP,TrumpApproval,8.478754286735066,14.272499783288554,-57.95136830581733,0.013110160827636719,0.332328
+140,Regression,River MLP,TrumpApproval,7.525552058981039,13.242333407520347,-51.44233495767236,0.013110160827636719,0.527456
+160,Regression,River MLP,TrumpApproval,6.729532853932534,12.401843141618142,-39.56324503441056,0.013110160827636719,0.7296090000000001
+180,Regression,River MLP,TrumpApproval,6.20494414148211,11.727398222866162,-30.855608065765253,0.013110160827636719,0.938725
+200,Regression,River MLP,TrumpApproval,5.707613016041334,11.135875265707485,-27.808506433676282,0.013110160827636719,1.173453
+220,Regression,River MLP,TrumpApproval,5.35235544657082,10.636236352263047,-27.34993958822678,0.013110160827636719,1.423387
+240,Regression,River MLP,TrumpApproval,4.997211310189409,10.191758203807838,-25.225868327846438,0.013110160827636719,1.696442
+260,Regression,River MLP,TrumpApproval,4.698339965696975,9.799142308635478,-23.570888426665658,0.013350486755371094,2.044166
+280,Regression,River MLP,TrumpApproval,4.429952698677103,9.448184269747657,-22.91569767610472,0.013350486755371094,2.398587
+300,Regression,River MLP,TrumpApproval,4.185436867704573,9.131292683908228,-20.968518634865898,0.013350486755371094,2.759636
+320,Regression,River MLP,TrumpApproval,3.989857840855361,8.848493522992882,-20.65027251080777,0.013350486755371094,3.127609
+340,Regression,River MLP,TrumpApproval,3.793510888989401,8.58729864958044,-20.548263158423392,0.013350486755371094,3.5072970000000003
+360,Regression,River MLP,TrumpApproval,3.624008920532304,8.350732680595982,-19.544713512132038,0.013350486755371094,3.994133
+380,Regression,River MLP,TrumpApproval,3.4723941591948395,8.130732570333006,-19.15022282865096,0.013350486755371094,4.488831
+400,Regression,River MLP,TrumpApproval,3.327129028584169,7.926491124989248,-18.691844486765735,0.013350486755371094,4.996594
+420,Regression,River MLP,TrumpApproval,3.1988914312464622,7.737168953530663,-18.383340677896445,0.013350486755371094,5.512642
+440,Regression,River MLP,TrumpApproval,3.0905418652204037,7.562941397323993,-17.185096454486196,0.013350486755371094,6.041213
+460,Regression,River MLP,TrumpApproval,2.9841087219087,7.398658950448711,-15.50384711789857,0.013350486755371094,6.671723
+480,Regression,River MLP,TrumpApproval,2.878027938067315,7.243616567021465,-14.455461195017083,0.013350486755371094,7.311147
+500,Regression,River MLP,TrumpApproval,2.790174040420949,7.099353406661882,-13.534510391092628,0.013350486755371094,7.962598
+520,Regression,River MLP,TrumpApproval,2.702735665583147,6.962851553400364,-13.005371203657658,0.013350486755371094,8.621042
+540,Regression,River MLP,TrumpApproval,2.619923274637493,6.8334980874356335,-12.440396167539378,0.013350486755371094,9.286045999999999
+560,Regression,River MLP,TrumpApproval,2.556848015725479,6.714676061099242,-12.286263553450382,0.013350486755371094,9.968405999999998
+580,Regression,River MLP,TrumpApproval,2.4920466556079988,6.599727625727584,-12.1527109643015,0.013350486755371094,10.662936999999998
+600,Regression,River MLP,TrumpApproval,2.4260558633236777,6.490118235625791,-11.578750092830703,0.013350486755371094,11.381531999999998
+620,Regression,River MLP,TrumpApproval,2.3708694907142864,6.387338726311831,-10.997792654674662,0.013350486755371094,12.131809999999998
+640,Regression,River MLP,TrumpApproval,2.309077397643504,6.287531812954472,-10.40846497658843,0.013350486755371094,12.902857999999998
+660,Regression,River MLP,TrumpApproval,2.253417256192923,6.192441467899733,-9.986430076809746,0.013350486755371094,13.765244
+680,Regression,River MLP,TrumpApproval,2.1933714736526424,6.100884478116631,-9.832475924452435,0.013350486755371094,14.638727
+700,Regression,River MLP,TrumpApproval,2.1444840100167193,6.014053532220149,-9.80279442231031,0.013350486755371094,15.530555
+720,Regression,River MLP,TrumpApproval,2.0889149793500317,5.930058413028094,-9.733901359629304,0.013350486755371094,16.434104
+740,Regression,River MLP,TrumpApproval,2.038014375475162,5.849577408393744,-9.43824097776182,0.013350486755371094,17.347853
+760,Regression,River MLP,TrumpApproval,1.990139846596363,5.772270602035659,-9.274280741061778,0.013350486755371094,18.296023
+780,Regression,River MLP,TrumpApproval,1.946515411702069,5.69815370877383,-9.05697999731458,0.013350486755371094,19.263123
+800,Regression,River MLP,TrumpApproval,1.9088971171085878,5.627293726045093,-8.897112526821198,0.013350486755371094,20.241821
+820,Regression,River MLP,TrumpApproval,1.8732261968689674,5.559226632327132,-8.765208356441784,0.013350486755371094,21.227083
+840,Regression,River MLP,TrumpApproval,1.8347271749400444,5.492864392938861,-8.621969919695442,0.013350486755371094,22.223141000000002
+860,Regression,River MLP,TrumpApproval,1.8001515928803729,5.4291765082898245,-8.383942958793503,0.013350486755371094,23.230427000000002
+880,Regression,River MLP,TrumpApproval,1.762610565031098,5.367211780988228,-8.125392758933815,0.013350486755371094,24.244373000000003
+900,Regression,River MLP,TrumpApproval,1.7278213800286457,5.307357454879676,-7.9606012045493255,0.013350486755371094,25.346781000000004
+920,Regression,River MLP,TrumpApproval,1.6959197142820022,5.249600105314111,-7.910676780558388,0.013350486755371094,26.455778000000002
+940,Regression,River MLP,TrumpApproval,1.6672680101890094,5.193857129216991,-7.796440957593809,0.013350486755371094,27.578615000000003
+960,Regression,River MLP,TrumpApproval,1.6372087427382507,5.139738169534271,-7.704147396017831,0.013350486755371094,28.708325000000002
+980,Regression,River MLP,TrumpApproval,1.6082702309133736,5.087224346398139,-7.692803163516414,0.013350486755371094,29.852185000000002
+1000,Regression,River MLP,TrumpApproval,1.582128560540168,5.036439630005545,-7.663534315499042,0.013350486755371094,31.047385000000002
+1001,Regression,River MLP,TrumpApproval,1.5805783932319006,5.033923389051291,-7.660658200179739,0.013350486755371094,32.243154000000004
+11,Regression,[baseline] Mean predictor,ChickWeights,4.664574314574316,12.707974531760701,-206.87879383707747,0.0004901885986328125,0.000258
+22,Regression,[baseline] Mean predictor,ChickWeights,2.767694704637076,9.018587183866769,-85.14025986830408,0.0004901885986328125,0.000737
+33,Regression,[baseline] Mean predictor,ChickWeights,2.3093367298127023,7.420500566500976,-37.24267181629702,0.0004901885986328125,0.00134
+44,Regression,[baseline] Mean predictor,ChickWeights,1.8923639683488078,6.441521936619904,-31.668094594906044,0.0004901885986328125,0.002066
+55,Regression,[baseline] Mean predictor,ChickWeights,2.1129412159858934,6.114058653243701,-6.297346571779499,0.0004901885986328125,0.0029100000000000003
+66,Regression,[baseline] Mean predictor,ChickWeights,2.832849782567835,6.236602142425367,-2.2730130120415795,0.0004901885986328125,0.0038720000000000004
+77,Regression,[baseline] Mean predictor,ChickWeights,3.4069290990236856,6.402381882180361,-1.3118663438824,0.0004901885986328125,0.004952000000000001
+88,Regression,[baseline] Mean predictor,ChickWeights,3.6503779711608075,6.321189272940957,-1.043267371916866,0.0004901885986328125,0.006149000000000001
+99,Regression,[baseline] Mean predictor,ChickWeights,4.035631404360372,6.4483291916176695,-0.7783857772357967,0.0004901885986328125,0.007464000000000001
+110,Regression,[baseline] Mean predictor,ChickWeights,4.693189868957898,7.0697740144659305,-0.49277927868413074,0.0004901885986328125,0.008896000000000001
+121,Regression,[baseline] Mean predictor,ChickWeights,5.274396860168236,7.6542276724395,-0.34762252544372596,0.0004901885986328125,0.010446
+132,Regression,[baseline] Mean predictor,ChickWeights,5.875758254207378,8.194624755054596,-0.2624191661321591,0.0004901885986328125,0.012113
+143,Regression,[baseline] Mean predictor,ChickWeights,6.530760796045927,8.870097879563003,-0.19803554240449484,0.0004901885986328125,0.013898
+154,Regression,[baseline] Mean predictor,ChickWeights,7.121466111912466,9.458403141043558,-0.15770278521517955,0.0004901885986328125,0.015801
+165,Regression,[baseline] Mean predictor,ChickWeights,7.772438504082036,10.375670403553157,-0.11989999304508925,0.0004901885986328125,0.017821999999999998
+176,Regression,[baseline] Mean predictor,ChickWeights,8.565827130563894,11.410434180005831,-0.09206765686265328,0.0004901885986328125,0.019960999999999996
+187,Regression,[baseline] Mean predictor,ChickWeights,9.429958588641576,12.495061319237752,-0.07221531716282037,0.0004901885986328125,0.022216999999999997
+198,Regression,[baseline] Mean predictor,ChickWeights,10.47731537859646,13.900491647656429,-0.05555027037575888,0.0004901885986328125,0.024589999999999997
+209,Regression,[baseline] Mean predictor,ChickWeights,11.43172675762076,15.229123619635446,-0.04445651287163721,0.0004901885986328125,0.027079
+220,Regression,[baseline] Mean predictor,ChickWeights,11.974320980081139,16.22368260926648,-0.03775608698471111,0.0004901885986328125,0.029685
+231,Regression,[baseline] Mean predictor,ChickWeights,12.9382196746461,17.489503190785292,-0.03157819728271183,0.0004901885986328125,0.032406
+242,Regression,[baseline] Mean predictor,ChickWeights,14.229204186206863,19.43725798629848,-0.02523677186741935,0.0004901885986328125,0.035243
+253,Regression,[baseline] Mean predictor,ChickWeights,15.339413196393396,20.820238312545918,-0.021649789303838762,0.0004901885986328125,0.041904
+264,Regression,[baseline] Mean predictor,ChickWeights,15.948617107030818,21.75817315507082,-0.019440185124094622,0.0004901885986328125,0.048726
+275,Regression,[baseline] Mean predictor,ChickWeights,16.794155127707494,23.16724301729152,-0.016999619323781356,0.0004901885986328125,0.055688
+286,Regression,[baseline] Mean predictor,ChickWeights,17.990009992534457,24.865985915258104,-0.014754713395529917,0.0004901885986328125,0.062787
+297,Regression,[baseline] Mean predictor,ChickWeights,19.34919450213405,26.676209297603677,-0.012890456560007202,0.0004901885986328125,0.070018
+308,Regression,[baseline] Mean predictor,ChickWeights,20.46881241431745,28.248013022827834,-0.011537481517321035,0.0004901885986328125,0.077383
+319,Regression,[baseline] Mean predictor,ChickWeights,20.993702124162965,29.638141143499492,-0.010503673119392376,0.0004901885986328125,0.08488399999999999
+330,Regression,[baseline] Mean predictor,ChickWeights,22.586872779548433,32.01796640002603,-0.009220237952050514,0.0004901885986328125,0.09251699999999999
+341,Regression,[baseline] Mean predictor,ChickWeights,23.973458872107372,33.821533603903084,-0.008387701903732392,0.0004901885986328125,0.10028199999999998
+352,Regression,[baseline] Mean predictor,ChickWeights,25.315991788770976,35.461698606860665,-0.007731302158646702,0.0004901885986328125,0.10817799999999998
+363,Regression,[baseline] Mean predictor,ChickWeights,25.615062978866305,35.981300981590465,-0.007443749031205149,0.0004901885986328125,0.11620599999999998
+374,Regression,[baseline] Mean predictor,ChickWeights,26.673321526932543,37.51836715700961,-0.006935846124255907,0.0004901885986328125,0.12436199999999997
+385,Regression,[baseline] Mean predictor,ChickWeights,28.27694482780972,39.8753298933956,-0.006332510983879436,0.0004901885986328125,0.13263999999999998
+396,Regression,[baseline] Mean predictor,ChickWeights,29.55612496209691,41.288487059450155,-0.005980181891907188,0.0004901885986328125,0.14104099999999997
+407,Regression,[baseline] Mean predictor,ChickWeights,30.561677112682855,42.81802042618151,-0.005646723150046551,0.0004901885986328125,0.14956599999999998
+418,Regression,[baseline] Mean predictor,ChickWeights,31.39346669137945,44.18765357092498,-0.0053697143301307815,0.0004901885986328125,0.15821399999999997
+429,Regression,[baseline] Mean predictor,ChickWeights,33.10612890637694,46.865579751152914,-0.004966366070605188,0.0004901885986328125,0.16698499999999997
+440,Regression,[baseline] Mean predictor,ChickWeights,34.54914638861108,48.61167278858254,-0.004716123854972665,0.0004901885986328125,0.17588299999999996
+451,Regression,[baseline] Mean predictor,ChickWeights,35.43263419295921,49.67507127970072,-0.004553693807187953,0.0004901885986328125,0.18490599999999996
+462,Regression,[baseline] Mean predictor,ChickWeights,36.308550382896186,51.2507761435036,-0.004357377489546899,0.0004901885986328125,0.19405499999999995
+473,Regression,[baseline] Mean predictor,ChickWeights,38.26330298063241,54.532250497281034,-0.004051661204895529,0.0004901885986328125,0.20332799999999995
+484,Regression,[baseline] Mean predictor,ChickWeights,39.598662348008276,56.08659790201894,-0.0039023944795495424,0.0004901885986328125,0.21272499999999994
+495,Regression,[baseline] Mean predictor,ChickWeights,40.94697327298068,57.823326559810994,-0.0037535911132069444,0.0004901885986328125,0.22224499999999994
+506,Regression,[baseline] Mean predictor,ChickWeights,41.42384714758024,58.679845942015916,-0.003665234721119459,0.0004901885986328125,0.23188899999999996
+517,Regression,[baseline] Mean predictor,ChickWeights,42.72663002099646,60.40151056768402,-0.0035345422299792872,0.0004901885986328125,0.24165999999999996
+528,Regression,[baseline] Mean predictor,ChickWeights,44.77321528369677,63.69509749878913,-0.0033415055563215112,0.0004901885986328125,0.25155399999999994
+539,Regression,[baseline] Mean predictor,ChickWeights,45.99579764939489,65.0494992510053,-0.0032526095626370655,0.0004901885986328125,0.26157099999999994
+550,Regression,[baseline] Mean predictor,ChickWeights,46.57020777663759,66.07332710234044,-0.0031815200825582313,0.0004901885986328125,0.2717109999999999
+561,Regression,[baseline] Mean predictor,ChickWeights,47.758257606406204,67.5643396193493,-0.0030950009187136196,0.0004901885986328125,0.28197199999999994
+572,Regression,[baseline] Mean predictor,ChickWeights,49.49138874897682,70.24569214117749,-0.002971942406188699,0.0004901885986328125,0.29235599999999995
+578,Regression,[baseline] Mean predictor,ChickWeights,50.250899455914585,71.11438743304103,-0.002929468639104371,0.0004901885986328125,0.30283499999999997
+20,Regression,[baseline] Mean predictor,TrumpApproval,2.695184981652336,9.807184976514188,-224.6021011118197,0.0004901885986328125,0.001338
+40,Regression,[baseline] Mean predictor,TrumpApproval,2.3994713447037435,7.102066178895935,-19.27845129783118,0.0004901885986328125,0.0038250000000000003
+60,Regression,[baseline] Mean predictor,TrumpApproval,1.8170744682035582,5.815253847056423,-17.329373299766118,0.0004901885986328125,0.00717
+80,Regression,[baseline] Mean predictor,TrumpApproval,1.604995404573344,5.081770494168446,-13.040545957103586,0.0004901885986328125,0.011356999999999999
+100,Regression,[baseline] Mean predictor,TrumpApproval,1.824259078948539,4.70488333223354,-6.5512954222403845,0.0004901885986328125,0.020929
+120,Regression,[baseline] Mean predictor,TrumpApproval,1.9187446081165878,4.412336880489357,-4.634185300646759,0.0004901885986328125,0.030834
+140,Regression,[baseline] Mean predictor,TrumpApproval,1.8761207739327506,4.13187920011476,-4.1056167996805835,0.0004901885986328125,0.041039
+160,Regression,[baseline] Mean predictor,TrumpApproval,1.961232939518506,3.9761734872745063,-3.1695661963674864,0.0004901885986328125,0.051538
+180,Regression,[baseline] Mean predictor,TrumpApproval,2.066134597500757,3.873731518767916,-2.4756944369169624,0.0004901885986328125,0.062312
+200,Regression,[baseline] Mean predictor,TrumpApproval,2.051125997923389,3.731810291394655,-2.23527456693896,0.0004901885986328125,0.073408
+220,Regression,[baseline] Mean predictor,TrumpApproval,1.9409519346841397,3.56902990398404,-2.19210047340805,0.0004901885986328125,0.084777
+240,Regression,[baseline] Mean predictor,TrumpApproval,1.9366756524315063,3.4612902974772624,-2.024876884626847,0.0004901885986328125,0.096419
+260,Regression,[baseline] Mean predictor,TrumpApproval,1.9250039777458068,3.363327951159923,-1.8945640461454523,0.0004901885986328125,0.108333
+280,Regression,[baseline] Mean predictor,TrumpApproval,1.8726934920539138,3.257010428159885,-1.8420037280027222,0.0004901885986328125,0.120517
+300,Regression,[baseline] Mean predictor,TrumpApproval,1.8907476896224937,3.1958821895815714,-1.6910252267675165,0.0004901885986328125,0.133002
+320,Regression,[baseline] Mean predictor,TrumpApproval,1.819623890420079,3.103812605138666,-1.663886258690169,0.0004901885986328125,0.145758
+340,Regression,[baseline] Mean predictor,TrumpApproval,1.7396293145937214,3.014220627768389,-1.654906383755708,0.0004901885986328125,0.158784
+360,Regression,[baseline] Mean predictor,TrumpApproval,1.7350691203787965,2.9569384317632506,-1.5759385016835008,0.0004901885986328125,0.172076
+380,Regression,[baseline] Mean predictor,TrumpApproval,1.6987131960417108,2.8893997308323693,-1.5446951110541192,0.0004901885986328125,0.185636
+400,Regression,[baseline] Mean predictor,TrumpApproval,1.673610627740774,2.82935583501861,-1.5089937655143242,0.0004901885986328125,0.199488
+420,Regression,[baseline] Mean predictor,TrumpApproval,1.6410137122925974,2.7701802079251965,-1.484737486096575,0.0004901885986328125,0.213608
+440,Regression,[baseline] Mean predictor,TrumpApproval,1.6565972573555454,2.7427790467379385,-1.391750010744973,0.0004901885986328125,0.227993
+460,Regression,[baseline] Mean predictor,TrumpApproval,1.699464840115161,2.7394674040138396,-1.2626191030939884,0.0004901885986328125,0.242643
+480,Regression,[baseline] Mean predictor,TrumpApproval,1.7224824441896143,2.7219018737730583,-1.182307732575659,0.0004901885986328125,0.25756
+500,Regression,[baseline] Mean predictor,TrumpApproval,1.7446092142173422,2.7058035442295596,-1.1113262021905803,0.0004901885986328125,0.272747
+520,Regression,[baseline] Mean predictor,TrumpApproval,1.7464998751860934,2.677192702589883,-1.0705208906620065,0.0004901885986328125,0.288233
+540,Regression,[baseline] Mean predictor,TrumpApproval,1.7535492786865425,2.653885630983747,-1.0271707062792519,0.0004901885986328125,0.303987
+560,Regression,[baseline] Mean predictor,TrumpApproval,1.7201019899937544,2.614359234374483,-1.0141103337708768,0.0004901885986328125,0.320009
+580,Regression,[baseline] Mean predictor,TrumpApproval,1.6887559504032665,2.5757257291728384,-1.0033760803823184,0.0004901885986328125,0.336298
+600,Regression,[baseline] Mean predictor,TrumpApproval,1.701917368353294,2.5614247637328695,-0.9592753712060649,0.0004901885986328125,0.35287999999999997
+620,Regression,[baseline] Mean predictor,TrumpApproval,1.7178157166185173,2.5513468959681562,-0.9142580419512063,0.0004901885986328125,0.369731
+640,Regression,[baseline] Mean predictor,TrumpApproval,1.7365901196485038,2.545046385321895,-0.8692105635365064,0.0004901885986328125,0.386852
+660,Regression,[baseline] Mean predictor,TrumpApproval,1.7465677425181807,2.532051562790666,-0.8368676529707118,0.0004901885986328125,0.40424
+680,Regression,[baseline] Mean predictor,TrumpApproval,1.731617734826669,2.5042261861708606,-0.8251107974736909,0.0004901885986328125,0.42189499999999996
+700,Regression,[baseline] Mean predictor,TrumpApproval,1.6973720107412233,2.4702678919797196,-0.8225927549994396,0.0004901885986328125,0.439849
+720,Regression,[baseline] Mean predictor,TrumpApproval,1.6698372433333928,2.4400355004771073,-0.81732226470892,0.0004901885986328125,0.458072
+740,Regression,[baseline] Mean predictor,TrumpApproval,1.6732482399922957,2.425592833263792,-0.7947920429290933,0.0004901885986328125,0.47656299999999996
+760,Regression,[baseline] Mean predictor,TrumpApproval,1.6653913599894004,2.404136439714782,-0.7822814452716051,0.0004901885986328125,0.49532099999999996
+780,Regression,[baseline] Mean predictor,TrumpApproval,1.6644612180457288,2.387561393188575,-0.7656652158374817,0.0004901885986328125,0.514347
+800,Regression,[baseline] Mean predictor,TrumpApproval,1.6556359332933146,2.368497267913513,-0.7532954885990883,0.0004901885986328125,0.533661
+820,Regression,[baseline] Mean predictor,TrumpApproval,1.6452077788467467,2.348678653798561,-0.7430103139622937,0.0004901885986328125,0.5532450000000001
+840,Regression,[baseline] Mean predictor,TrumpApproval,1.6374623223784903,2.3305035344735936,-0.7320713255917544,0.0004901885986328125,0.5730930000000001
+860,Regression,[baseline] Mean predictor,TrumpApproval,1.6419505315856449,2.3202080137162757,-0.7138439732116804,0.0004901885986328125,0.6284980000000001
+880,Regression,[baseline] Mean predictor,TrumpApproval,1.6490002164922652,2.3126155324510744,-0.6941855677649247,0.0004901885986328125,0.6842080000000001
+900,Regression,[baseline] Mean predictor,TrumpApproval,1.6474991175923384,2.299197536504521,-0.6816400531907807,0.0004901885986328125,0.7401880000000002
+920,Regression,[baseline] Mean predictor,TrumpApproval,1.6301006788336792,2.2779225390149764,-0.6777843948800273,0.0004901885986328125,0.7964830000000002
+940,Regression,[baseline] Mean predictor,TrumpApproval,1.6221876471839873,2.2623787372500574,-0.6690049120995847,0.0004901885986328125,0.8530460000000002
+960,Regression,[baseline] Mean predictor,TrumpApproval,1.6124120493571745,2.245866476718547,-0.6619276404267609,0.0004901885986328125,0.9098760000000002
+980,Regression,[baseline] Mean predictor,TrumpApproval,1.5867001120604314,2.223758235975506,-0.661013659831075,0.0004901885986328125,0.9669740000000002
+1000,Regression,[baseline] Mean predictor,TrumpApproval,1.5681359363812417,2.2037391763141216,-0.6587014308970958,0.0004901885986328125,1.0243380000000002
+1001,Regression,[baseline] Mean predictor,TrumpApproval,1.567554989468773,2.202858861923226,-0.6584830635688459,0.0004901885986328125,1.081765