Eddie Bergman: Regression testing (#1233)

automl · Sep 3, 2021 · 1011aee · 1011aee
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diff --git a/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip b/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip
diff --git a/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip b/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip
diff --git a/development/_images/sphx_glr_example_inspect_predictions_001.png b/development/_images/sphx_glr_example_inspect_predictions_001.png
diff --git a/development/_images/sphx_glr_example_inspect_predictions_002.png b/development/_images/sphx_glr_example_inspect_predictions_002.png
diff --git a/development/_images/sphx_glr_example_inspect_predictions_003.png b/development/_images/sphx_glr_example_inspect_predictions_003.png
diff --git a/development/_images/sphx_glr_example_inspect_predictions_thumb.png b/development/_images/sphx_glr_example_inspect_predictions_thumb.png
diff --git a/development/_images/sphx_glr_example_pandas_train_test_001.png b/development/_images/sphx_glr_example_pandas_train_test_001.png
diff --git a/development/_images/sphx_glr_example_pandas_train_test_thumb.png b/development/_images/sphx_glr_example_pandas_train_test_thumb.png
diff --git a/development/_images/sphx_glr_example_regression_001.png b/development/_images/sphx_glr_example_regression_001.png
diff --git a/development/_images/sphx_glr_example_regression_thumb.png b/development/_images/sphx_glr_example_regression_thumb.png
diff --git a/development/_sources/examples/20_basic/example_classification.rst.txt b/development/_sources/examples/20_basic/example_classification.rst.txt
diff --git a/development/_sources/examples/20_basic/example_multilabel_classification.rst.txt b/development/_sources/examples/20_basic/example_multilabel_classification.rst.txt
@@ -157,7 +157,7 @@ View the models found by auto-sklearn
 
               rank  ensemble_weight           type     cost  duration
     model_id                                                         
-    2            1              1.0  random_forest  0.44715  4.298346
+    2            1              1.0  random_forest  0.44715  3.692611
 
 
 
@@ -265,7 +265,7 @@ Get the Score of the final ensemble
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  15.010 seconds)
+   **Total running time of the script:** ( 0 minutes  13.064 seconds)
 
 
 .. _sphx_glr_download_examples_20_basic_example_multilabel_classification.py:

diff --git a/development/_sources/examples/20_basic/example_multioutput_regression.rst.txt b/development/_sources/examples/20_basic/example_multioutput_regression.rst.txt
@@ -122,10 +122,11 @@ View the models found by auto-sklearn
 
  .. code-block:: none
 
-              rank  ensemble_weight              type          cost  duration
-    model_id                                                                 
-    12           1             0.82  gaussian_process  2.116595e-10  7.058984
-    16           2             0.18  gaussian_process  3.207687e-10  6.269364
+              rank  ensemble_weight              type      cost  duration
+    model_id                                                             
+    12           1             0.96  gaussian_process  0.062154  2.069102
+    2            2             0.02     random_forest  0.145567  2.539505
+    23           3             0.02  gaussian_process  0.244557  3.924972
 
 
 
@@ -152,14 +153,21 @@ Print the final ensemble constructed by auto-sklearn
 
  .. code-block:: none
 
-    [(0.820000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_regression', 'regressor:__choice__': 'gaussian_process', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'median', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:extra_trees_preproc_for_regression:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_regression:criterion': 'mse', 'feature_preprocessor:extra_trees_preproc_for_regression:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_regression:max_features': 0.6296652738937326, 'feature_preprocessor:extra_trees_preproc_for_regression:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_regression:min_samples_leaf': 15, 'feature_preprocessor:extra_trees_preproc_for_regression:min_samples_split': 7, 'feature_preprocessor:extra_trees_preproc_for_regression:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_regression:n_estimators': 100, 'regressor:gaussian_process:alpha': 1.0001184179669579e-14, 'regressor:gaussian_process:thetaL': 2.0039452151237183e-06, 'regressor:gaussian_process:thetaU': 92.9575073260599, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.08568852702006044},
+    [(0.960000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_regression', 'regressor:__choice__': 'gaussian_process', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'median', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:extra_trees_preproc_for_regression:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_regression:criterion': 'mse', 'feature_preprocessor:extra_trees_preproc_for_regression:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_regression:max_features': 0.6296652738937326, 'feature_preprocessor:extra_trees_preproc_for_regression:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_regression:min_samples_leaf': 15, 'feature_preprocessor:extra_trees_preproc_for_regression:min_samples_split': 7, 'feature_preprocessor:extra_trees_preproc_for_regression:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_regression:n_estimators': 100, 'regressor:gaussian_process:alpha': 1.0001184179669579e-14, 'regressor:gaussian_process:thetaL': 2.003945215123722e-06, 'regressor:gaussian_process:thetaU': 92.9575073260599, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.08568852702006044},
     dataset_properties={
       'task': 5,
       'sparse': False,
       'multioutput': True,
       'target_type': 'regression',
       'signed': False})),
-    (0.180000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'gaussian_process', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'median', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'regressor:gaussian_process:alpha': 4.624674659544354e-13, 'regressor:gaussian_process:thetaL': 3.9399009115324753e-05, 'regressor:gaussian_process:thetaU': 28202.137936369556, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.13899586898131186},
+    (0.020000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'random_forest', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'regressor:random_forest:bootstrap': 'True', 'regressor:random_forest:criterion': 'mse', 'regressor:random_forest:max_depth': 'None', 'regressor:random_forest:max_features': 1.0, 'regressor:random_forest:max_leaf_nodes': 'None', 'regressor:random_forest:min_impurity_decrease': 0.0, 'regressor:random_forest:min_samples_leaf': 1, 'regressor:random_forest:min_samples_split': 2, 'regressor:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01},
+    dataset_properties={
+      'task': 5,
+      'sparse': False,
+      'multioutput': True,
+      'target_type': 'regression',
+      'signed': False})),
+    (0.020000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'pca', 'regressor:__choice__': 'gaussian_process', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:pca:keep_variance': 0.897057584116977, 'feature_preprocessor:pca:whiten': 'True', 'regressor:gaussian_process:alpha': 4.023867631093007e-06, 'regressor:gaussian_process:thetaL': 2.646485556446059e-07, 'regressor:gaussian_process:thetaU': 69187.74971189063},
     dataset_properties={
       'task': 5,
       'sparse': False,
@@ -194,7 +202,7 @@ Get the Score of the final ensemble
 
  .. code-block:: none
 
-    R2 score: 0.9999999998331437
+    R2 score: 0.9475591377934744
 
 
 
@@ -417,7 +425,7 @@ Get the configuration space
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  3.877 seconds)
+   **Total running time of the script:** ( 1 minutes  55.279 seconds)
 
 
 .. _sphx_glr_download_examples_20_basic_example_multioutput_regression.py: