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Eddie Bergman: Fix random state not being used for sampling configurations (#1329)
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development/_sources/examples/20_basic/example_classification.rst.txt

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development/_sources/examples/20_basic/example_multilabel_classification.rst.txt

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@@ -154,7 +154,7 @@ View the models found by auto-sklearn
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rank ensemble_weight type cost duration
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model_id
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2 1 1.0 random_forest 0.447294 3.259168
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2 1 1.0 random_forest 0.447294 3.782916
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@@ -262,7 +262,7 @@ Get the Score of the final ensemble
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 14.171 seconds)
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**Total running time of the script:** ( 0 minutes 15.627 seconds)
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.. _sphx_glr_download_examples_20_basic_example_multilabel_classification.py:

development/_sources/examples/20_basic/example_multioutput_regression.rst.txt

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@@ -122,9 +122,14 @@ View the models found by auto-sklearn
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.. code-block:: none
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rank ensemble_weight type cost duration
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model_id
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11 1 1.0 gaussian_process 4.436846e-10 9.897039
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rank ensemble_weight type cost duration
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model_id
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2 1 0.74 random_forest 0.105222 2.568839
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20 2 0.02 extra_trees 0.126052 1.365298
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5 3 0.06 k_nearest_neighbors 0.277803 0.518441
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8 4 0.04 extra_trees 0.308847 1.598460
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22 5 0.10 k_nearest_neighbors 0.377291 0.517786
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14 6 0.04 k_nearest_neighbors 0.548478 0.893792
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@@ -151,7 +156,42 @@ Print the final ensemble constructed by auto-sklearn
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.. code-block:: none
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[(1.000000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'gaussian_process', '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': 'most_frequent', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'regressor:gaussian_process:alpha': 1.6650724498551164e-11, 'regressor:gaussian_process:thetaL': 5.222627524598125e-10, 'regressor:gaussian_process:thetaU': 5801.524168449955, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0809214996879808, 'data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_max': 0.9020530113478731, 'data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_min': 0.10288728233229412},
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[(0.740000, 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},
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dataset_properties={
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'task': 5,
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'sparse': False,
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'multioutput': True,
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'target_type': 'regression',
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'signed': False})),
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(0.100000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'polynomial', 'regressor:__choice__': 'k_nearest_neighbors', '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': 'most_frequent', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'True', 'regressor:k_nearest_neighbors:n_neighbors': 1, 'regressor:k_nearest_neighbors:p': 1, 'regressor:k_nearest_neighbors:weights': 'uniform', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0003383450128800807},
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dataset_properties={
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'task': 5,
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'sparse': False,
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'multioutput': True,
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'target_type': 'regression',
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'signed': False})),
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(0.060000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'pca', 'regressor:__choice__': 'k_nearest_neighbors', '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': 'mean', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:pca:keep_variance': 0.8772654126094648, 'feature_preprocessor:pca:whiten': 'True', 'regressor:k_nearest_neighbors:n_neighbors': 14, 'regressor:k_nearest_neighbors:p': 1, 'regressor:k_nearest_neighbors:weights': 'uniform'},
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dataset_properties={
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'task': 5,
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'sparse': False,
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'multioutput': True,
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'target_type': 'regression',
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'signed': False})),
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(0.040000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'fast_ica', 'regressor:__choice__': 'extra_trees', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'median', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:fast_ica:algorithm': 'parallel', 'feature_preprocessor:fast_ica:fun': 'cube', 'feature_preprocessor:fast_ica:whiten': 'True', 'regressor:extra_trees:bootstrap': 'True', 'regressor:extra_trees:criterion': 'friedman_mse', 'regressor:extra_trees:max_depth': 'None', 'regressor:extra_trees:max_features': 0.5507241840323179, 'regressor:extra_trees:max_leaf_nodes': 'None', 'regressor:extra_trees:min_impurity_decrease': 0.0, 'regressor:extra_trees:min_samples_leaf': 1, 'regressor:extra_trees:min_samples_split': 13, 'regressor:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:fast_ica:n_components': 1530},
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dataset_properties={
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'task': 5,
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'sparse': False,
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'multioutput': True,
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'target_type': 'regression',
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'signed': False})),
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(0.040000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'fast_ica', 'regressor:__choice__': 'k_nearest_neighbors', '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': 'most_frequent', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:fast_ica:algorithm': 'deflation', 'feature_preprocessor:fast_ica:fun': 'logcosh', 'feature_preprocessor:fast_ica:whiten': 'True', 'regressor:k_nearest_neighbors:n_neighbors': 1, 'regressor:k_nearest_neighbors:p': 1, 'regressor:k_nearest_neighbors:weights': 'distance', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.00024939850901091595, 'feature_preprocessor:fast_ica:n_components': 563},
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dataset_properties={
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'task': 5,
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'sparse': False,
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'multioutput': True,
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'target_type': 'regression',
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'signed': False})),
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(0.020000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'extra_trees', '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': 'mean', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'standardize', 'regressor:extra_trees:bootstrap': 'True', 'regressor:extra_trees:criterion': 'friedman_mse', 'regressor:extra_trees:max_depth': 'None', 'regressor:extra_trees:max_features': 0.9636134380703354, 'regressor:extra_trees:max_leaf_nodes': 'None', 'regressor:extra_trees:min_impurity_decrease': 0.0, 'regressor:extra_trees:min_samples_leaf': 1, 'regressor:extra_trees:min_samples_split': 17, 'regressor:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.014024988684708958},
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dataset_properties={
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'task': 5,
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@@ -186,7 +226,7 @@ Get the Score of the final ensemble
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.. code-block:: none
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R2 score: 0.9999999995269687
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R2 score: 0.8979526772328041
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 1 minutes 54.019 seconds)
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**Total running time of the script:** ( 2 minutes 19.828 seconds)
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.. _sphx_glr_download_examples_20_basic_example_multioutput_regression.py:

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