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fix string -> int #336

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fix string -> int #336

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c0e9b15
fix string -> int
MrAE Oct 2, 2019
aa4f5a1
Merge branch 'staging' into jlp/patch-20191002
MrAE Nov 21, 2019
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23 changes: 12 additions & 11 deletions docs/demos/S-RerF/MNIST_classification_using_structured_RerF.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,8 @@
"train_samples = 5000\n",
"\n",
"# Load data from https://www.openml.org/d/554\n",
"X, y = fetch_openml('mnist_784', version=1, return_X_y=True)"
"X, y = fetch_openml('mnist_784', version=1, return_X_y=True)\n",
"y = y.astype(int)"
]
},
{
Expand Down Expand Up @@ -73,12 +74,12 @@
"output_type": "stream",
"text": [
"rerfClassifier(feature_combinations=1.5, image_height=None, image_width=None,\n",
" max_depth=None, max_features='auto', min_parent=1,\n",
" max_depth=None, max_features='auto', min_samples_split=1,\n",
" n_estimators=100, n_jobs=8, oob_score=False,\n",
" patch_height_max=None, patch_height_min=1, patch_width_max=None,\n",
" patch_width_min=1, projection_matrix='Base', random_state=None)\n",
"rerfClassifier(feature_combinations=1.5, image_height=28, image_width=28,\n",
" max_depth=None, max_features='auto', min_parent=1,\n",
" max_depth=None, max_features='auto', min_samples_split=1,\n",
" n_estimators=100, n_jobs=8, oob_score=False, patch_height_max=5,\n",
" patch_height_min=1, patch_width_max=5, patch_width_min=1,\n",
" projection_matrix='S-RerF', random_state=None)\n"
Expand Down Expand Up @@ -110,7 +111,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"run time rerf 0.7958900928497314\n"
"run time rerf 1.1266508102416992\n"
]
}
],
Expand All @@ -130,7 +131,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"run time s_rerf 3.6138932704925537\n"
"run time s_rerf 6.353916883468628\n"
]
}
],
Expand Down Expand Up @@ -158,10 +159,10 @@
}
],
"source": [
"train_acc_rerf = clf_rerf.score(X_train, y_train.astype(int))\n",
"train_acc_rerf = clf_rerf.score(X_train, y_train)\n",
"print(\"train_acc rerf\", train_acc_rerf)\n",
"\n",
"train_acc_s_rerf = clf_s_rerf.score(X_train, y_train.astype(int))\n",
"train_acc_s_rerf = clf_s_rerf.score(X_train, y_train)\n",
"print(\"train_acc s_rerf\", train_acc_s_rerf)"
]
},
Expand All @@ -176,18 +177,18 @@
"name": "stdout",
"output_type": "stream",
"text": [
"score rerf 0.9361\n",
"score s_rerf 0.9427\n"
"score rerf 0.9376\n",
"score s_rerf 0.9436\n"
]
}
],
"source": [
"# sparsity = np.mean(clf.coef_ == 0) * 100\n",
"score = clf_rerf.score(X_test, y_test.astype(int))\n",
"score = clf_rerf.score(X_test, y_test)\n",
"print(\"score rerf\", score)\n",
"\n",
"# sparsity = np.mean(clf.coef_ == 0) * 100\n",
"score = clf_s_rerf.score(X_test, y_test.astype(int))\n",
"score = clf_s_rerf.score(X_test, y_test)\n",
"print(\"score s_rerf\", score)"
]
}
Expand Down