diff --git a/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip b/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip index 87ac142ee2..b26a4b076d 100644 Binary files a/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip and b/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip differ diff --git a/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip b/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip index ca5d094166..9bff626a81 100644 Binary files a/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip and b/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip differ diff --git a/development/_images/sphx_glr_example_pandas_train_test_001.png b/development/_images/sphx_glr_example_pandas_train_test_001.png index a1d3817dd1..e30a0be531 100644 Binary files a/development/_images/sphx_glr_example_pandas_train_test_001.png and b/development/_images/sphx_glr_example_pandas_train_test_001.png differ diff --git a/development/_images/sphx_glr_example_pandas_train_test_thumb.png b/development/_images/sphx_glr_example_pandas_train_test_thumb.png index e354401359..602419cddc 100644 Binary files a/development/_images/sphx_glr_example_pandas_train_test_thumb.png and b/development/_images/sphx_glr_example_pandas_train_test_thumb.png differ diff --git a/development/_sources/examples/20_basic/example_classification.rst.txt b/development/_sources/examples/20_basic/example_classification.rst.txt index a18e40fc48..83f766df61 100644 --- a/development/_sources/examples/20_basic/example_classification.rst.txt +++ b/development/_sources/examples/20_basic/example_classification.rst.txt @@ -25,7 +25,15 @@ The following example shows how to fit a simple classification model with .. code-block:: none - [(0.340000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.7304811343030777, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 3, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7202654714984674, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.21555973677200435, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'average', 'feature_preprocessor:feature_agglomeration:n_clusters': 149, 'feature_preprocessor:feature_agglomeration:pooling_func': 'median'}, + [WARNING] [2020-12-16 15:41:21,210:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 15:41:21,216:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:41:21,219:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 15:41:21,229:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 15:41:21,317:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 15:41:21,318:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 15:41:21,318:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:41:21,318:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [(0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 0.0001363185819149026, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.00018009776276177523, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 115, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'ward', 'feature_preprocessor:feature_agglomeration:n_clusters': 182, 'feature_preprocessor:feature_agglomeration:pooling_func': 'mean', 'classifier:mlp:validation_fraction': 0.1}, dataset_properties={ 'task': 1, 'sparse': False, @@ -33,7 +41,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.260000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 8.495727973549814e-08, 'classifier:gradient_boosting:learning_rate': 0.10895774269386836, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 17, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.009766287299931831, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 917, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False', 'classifier:gradient_boosting:n_iter_no_change': 16, 'classifier:gradient_boosting:validation_fraction': 0.018763788815745606}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.926283631486858, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 7, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.16265262021972576}, dataset_properties={ 'task': 1, 'sparse': False, @@ -41,7 +49,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 1.944632809484799e-07, 'classifier:gradient_boosting:learning_rate': 0.06023679587502036, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 28, 'classifier:gradient_boosting:min_samples_leaf': 193, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False', 'classifier:gradient_boosting:n_iter_no_change': 15, 'classifier:gradient_boosting:validation_fraction': 0.0639715328873465}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5805882119281688, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.11533421526707399, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'gini', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.8490063449951434, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 9, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -49,7 +57,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5707983257382487, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 3, 'classifier:extra_trees:min_samples_split': 11, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -57,7 +65,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 10, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1000, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'True'}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:mlp:activation': 'relu', 'classifier:mlp:alpha': 4.2841884333778574e-06, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'train', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.0011804284312897009, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 263, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.004071801722749603, 'feature_preprocessor:feature_agglomeration:affinity': 'manhattan', 'feature_preprocessor:feature_agglomeration:linkage': 'average', 'feature_preprocessor:feature_agglomeration:n_clusters': 338, 'feature_preprocessor:feature_agglomeration:pooling_func': 'mean'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -65,7 +73,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'qda', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:qda:reg_param': 0.563056219822946, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.32793677336996485}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'fast_ica', 'classifier:mlp:activation': 'relu', 'classifier:mlp:alpha': 0.0017940473175767063, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 2, 'classifier:mlp:learning_rate_init': 0.0004684917334431039, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 101, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:fast_ica:algorithm': 'parallel', 'feature_preprocessor:fast_ica:fun': 'exp', 'feature_preprocessor:fast_ica:whiten': 'False', 'classifier:mlp:validation_fraction': 0.1}, dataset_properties={ 'task': 1, 'sparse': False, @@ -73,7 +81,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.21772092350860472, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 14, 'classifier:random_forest:min_samples_split': 17, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0020488212891693275, 'feature_preprocessor:liblinear_svc_preprocessor:C': 33.74257606530722, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 8.740452966205111e-05}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.43999367631975456, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'True', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.8134515743047006, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 9, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 20, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -81,7 +89,7 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'kernel_pca', 'classifier:passive_aggressive:C': 1.9137257120393358, 'classifier:passive_aggressive:average': 'True', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.00012613872674401282, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.013158489866755073, 'feature_preprocessor:kernel_pca:kernel': 'rbf', 'feature_preprocessor:kernel_pca:n_components': 651, 'feature_preprocessor:kernel_pca:gamma': 0.08989386584219308}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.993803313878608, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 20, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.41826215858914706, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7305615609807856, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.25595970768123566, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'True'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -89,7 +97,103 @@ The following example shows how to fit a simple classification model with 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 0.0006322356877253852, 'classifier:gradient_boosting:learning_rate': 0.02155479872417127, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 15, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'random_trees_embedding', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 937, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'uniform', 'feature_preprocessor:random_trees_embedding:bootstrap': 'True', 'feature_preprocessor:random_trees_embedding:max_depth': 5, 'feature_preprocessor:random_trees_embedding:max_leaf_nodes': 'None', 'feature_preprocessor:random_trees_embedding:min_samples_leaf': 1, 'feature_preprocessor:random_trees_embedding:min_samples_split': 2, 'feature_preprocessor:random_trees_embedding:min_weight_fraction_leaf': 1.0, 'feature_preprocessor:random_trees_embedding:n_estimators': 10}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 1.0647401999412075e-10, 'classifier:gradient_boosting:learning_rate': 0.08291320147381159, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 39, 'classifier:gradient_boosting:min_samples_leaf': 20, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.008520698757932555, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7710965306105907, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.257333974790539, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'ward', 'feature_preprocessor:feature_agglomeration:n_clusters': 25, 'feature_preprocessor:feature_agglomeration:pooling_func': 'max'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 0.4635442279519353, 'classifier:gradient_boosting:learning_rate': 0.09809681787962342, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 328, 'classifier:gradient_boosting:min_samples_leaf': 2, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0208475757765491, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.989729761503726, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 19, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 5, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100, 'classifier:gradient_boosting:n_iter_no_change': 2}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'fast_ica', 'classifier:mlp:activation': 'relu', 'classifier:mlp:alpha': 0.02847755502162456, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'train', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 2, 'classifier:mlp:learning_rate_init': 0.000421568792103947, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 123, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:fast_ica:algorithm': 'parallel', 'feature_preprocessor:fast_ica:fun': 'exp', 'feature_preprocessor:fast_ica:whiten': 'False'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:passive_aggressive:C': 0.14268277711454813, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.0002600768160857831, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0070580904199417415}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'select_rates_classification', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.562561668029056, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 15, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:select_rates_classification:alpha': 0.32106218519214325, 'feature_preprocessor:select_rates_classification:score_func': 'chi2', 'feature_preprocessor:select_rates_classification:mode': 'fwe'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.971348315581384, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 19, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'select_percentile_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.49138075723513286, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 6, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.42693600390988135, 'feature_preprocessor:select_percentile_classification:percentile': 56.97947373958566, 'feature_preprocessor:select_percentile_classification:score_func': 'mutual_info'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 2.5550223982458062e-06, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'train', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.00027271287919467994, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 54, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.017116661677715188, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.7171678618990129, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 4, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 17, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.4775492074518431, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.015996368052062886, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7845396961078424, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.25545052141264185, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.5662900693317384, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 7, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 0.005326508887463406, 'classifier:gradient_boosting:learning_rate': 0.060800813211425456, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 5, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:liblinear_svc_preprocessor:C': 13.550960330919455, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 1.2958033930435781e-05, 'classifier:gradient_boosting:n_iter_no_change': 5}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.9292309396985746, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 1, 'classifier:extra_trees:min_samples_split': 10, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.032719158639429445, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.9929881254946676, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -153,7 +257,7 @@ The following example shows how to fit a simple classification model with .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 1 minutes 55.477 seconds) + **Total running time of the script:** ( 1 minutes 59.910 seconds) .. _sphx_glr_download_examples_20_basic_example_classification.py: diff --git a/development/_sources/examples/20_basic/example_multilabel_classification.rst.txt b/development/_sources/examples/20_basic/example_multilabel_classification.rst.txt index 2beeef5dfe..f2f7a351e7 100644 --- a/development/_sources/examples/20_basic/example_multilabel_classification.rst.txt +++ b/development/_sources/examples/20_basic/example_multilabel_classification.rst.txt @@ -27,7 +27,7 @@ problem. Details on multilabel classification can be found .. code-block:: none type_of_target=multilabel-indicator - [WARNING] [2020-12-11 17:25:12,368:AutoML(1):reuters] Capping the per_run_time_limit to 29.0 to have time for a least 2 models in each process. + [WARNING] [2020-12-16 15:43:26,831:AutoML(1):reuters] Capping the per_run_time_limit to 29.0 to have time for a least 2 models in each process. [(1.000000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, dataset_properties={ 'task': 3, @@ -131,7 +131,7 @@ problem. Details on multilabel classification can be found .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 19.850 seconds) + **Total running time of the script:** ( 0 minutes 18.793 seconds) .. _sphx_glr_download_examples_20_basic_example_multilabel_classification.py: diff --git a/development/_sources/examples/20_basic/example_regression.rst.txt b/development/_sources/examples/20_basic/example_regression.rst.txt index 088c2ef02c..8e2cd79c7e 100644 --- a/development/_sources/examples/20_basic/example_regression.rst.txt +++ b/development/_sources/examples/20_basic/example_regression.rst.txt @@ -27,45 +27,50 @@ The following example shows how to fit a simple regression model with /opt/hostedtoolcache/Python/3.8.6/x64/lib/python3.8/site-packages/pyparsing.py:3190: FutureWarning: Possible set intersection at position 3 self.re = re.compile(self.reString) - [WARNING] [2020-12-11 17:21:09,863:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 45 not found - [WARNING] [2020-12-11 17:21:09,863:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 17 not found - [WARNING] [2020-12-11 17:21:09,865:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 24 not found - [(0.280000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'select_rates_regression', 'regressor:__choice__': 'adaboost', 'feature_preprocessor:select_rates_regression:alpha': 0.13294870400704156, 'feature_preprocessor:select_rates_regression:mode': 'fwe', 'feature_preprocessor:select_rates_regression:score_func': 'f_regression', 'regressor:adaboost:learning_rate': 0.47982456668237294, 'regressor:adaboost:loss': 'exponential', 'regressor:adaboost:max_depth': 6, 'regressor:adaboost:n_estimators': 178}, + [WARNING] [2020-12-16 15:39:26,474:autosklearn.metalearning.metalearning.meta_base] Dataset boston already in meta-data. Removing occurence. + [WARNING] [2020-12-16 15:39:26,505:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance aloi + [WARNING] [2020-12-16 15:39:26,509:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance flora + [WARNING] [2020-12-16 15:39:26,514:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-100852 + [WARNING] [2020-12-16 15:39:26,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-10475 + [WARNING] [2020-12-16 15:39:26,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-10502 + [WARNING] [2020-12-16 15:39:26,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-10809 + [WARNING] [2020-12-16 15:39:26,516:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-10980 + [WARNING] [2020-12-16 15:39:26,516:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-11 + [WARNING] [2020-12-16 15:39:26,517:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-11626 + [WARNING] [2020-12-16 15:39:26,517:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-12569 + [WARNING] [2020-12-16 15:39:26,518:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-12947 + [WARNING] [2020-12-16 15:39:26,518:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-12968 + [WARNING] [2020-12-16 15:39:26,518:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-163 + [WARNING] [2020-12-16 15:39:26,519:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance qsar-tid-72 + [WARNING] [2020-12-16 15:39:26,570:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-11 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-10980 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-72 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-163 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-10502 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-12947 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-10475 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-12569 + [WARNING] [2020-12-16 15:39:26,571:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-100852 + [WARNING] [2020-12-16 15:39:26,572:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-12968 + [WARNING] [2020-12-16 15:39:26,572:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-10809 + [WARNING] [2020-12-16 15:39:26,572:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance qsar-tid-11626 + [WARNING] [2020-12-16 15:39:26,572:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance aloi + [WARNING] [2020-12-16 15:39:26,572:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance flora + [(0.640000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01, '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}, dataset_properties={ 'task': 4, 'sparse': False, 'multioutput': False, 'target_type': 'regression', 'signed': False})), - (0.200000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'libsvm_svr', 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.014087234899150132, 'regressor:libsvm_svr:C': 243.80018215429655, 'regressor:libsvm_svr:epsilon': 0.0010313680328976054, 'regressor:libsvm_svr:kernel': 'rbf', 'regressor:libsvm_svr:max_iter': -1, 'regressor:libsvm_svr:shrinking': 'True', 'regressor:libsvm_svr:tol': 0.0003015355281210108, 'regressor:libsvm_svr:degree': 5, 'regressor:libsvm_svr:gamma': 0.12602136380125653}, + (0.200000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'polynomial', 'regressor:__choice__': 'gaussian_process', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'True', 'regressor:gaussian_process:alpha': 0.037731974209709904, 'regressor:gaussian_process:thetaL': 5.002213042554931e-07, 'regressor:gaussian_process:thetaU': 22409.945864393645}, dataset_properties={ 'task': 4, 'sparse': False, 'multioutput': False, 'target_type': 'regression', 'signed': False})), - (0.180000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'select_rates_regression', 'regressor:__choice__': 'adaboost', 'feature_preprocessor:select_rates_regression:alpha': 0.13294870400704156, 'feature_preprocessor:select_rates_regression:mode': 'fwe', 'feature_preprocessor:select_rates_regression:score_func': 'f_regression', 'regressor:adaboost:learning_rate': 0.47982456668237294, 'regressor:adaboost:loss': 'square', 'regressor:adaboost:max_depth': 10, 'regressor:adaboost:n_estimators': 143}, - dataset_properties={ - 'task': 4, - 'sparse': False, - 'multioutput': False, - 'target_type': 'regression', - 'signed': False})), - (0.140000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'select_rates_regression', 'regressor:__choice__': 'gradient_boosting', 'feature_preprocessor:select_rates_regression:alpha': 0.12022046696839699, 'feature_preprocessor:select_rates_regression:mode': 'fdr', 'feature_preprocessor:select_rates_regression:score_func': 'f_regression', 'regressor:gradient_boosting:early_stop': 'off', 'regressor:gradient_boosting:l2_regularization': 9.732836733778985e-06, 'regressor:gradient_boosting:learning_rate': 0.07118635674179737, 'regressor:gradient_boosting:loss': 'least_squares', 'regressor:gradient_boosting:max_bins': 255, 'regressor:gradient_boosting:max_depth': 'None', 'regressor:gradient_boosting:max_leaf_nodes': 9, 'regressor:gradient_boosting:min_samples_leaf': 6, 'regressor:gradient_boosting:scoring': 'loss', 'regressor:gradient_boosting:tol': 1e-07}, - dataset_properties={ - 'task': 4, - 'sparse': False, - 'multioutput': False, - 'target_type': 'regression', - 'signed': False})), - (0.120000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'fast_ica', 'regressor:__choice__': 'gradient_boosting', 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7049491520337817, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.23602880130851764, 'feature_preprocessor:fast_ica:algorithm': 'deflation', 'feature_preprocessor:fast_ica:fun': 'cube', 'feature_preprocessor:fast_ica:whiten': 'False', 'regressor:gradient_boosting:early_stop': 'off', 'regressor:gradient_boosting:l2_regularization': 4.696295762197504e-10, 'regressor:gradient_boosting:learning_rate': 0.03269357604116943, 'regressor:gradient_boosting:loss': 'least_squares', 'regressor:gradient_boosting:max_bins': 255, 'regressor:gradient_boosting:max_depth': 'None', 'regressor:gradient_boosting:max_leaf_nodes': 32, 'regressor:gradient_boosting:min_samples_leaf': 14, 'regressor:gradient_boosting:scoring': 'loss', 'regressor:gradient_boosting:tol': 1e-07}, - dataset_properties={ - 'task': 4, - 'sparse': False, - 'multioutput': False, - 'target_type': 'regression', - 'signed': False})), - (0.080000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'regressor:__choice__': 'gradient_boosting', 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1425, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'uniform', 'feature_preprocessor:feature_agglomeration:affinity': 'cosine', 'feature_preprocessor:feature_agglomeration:linkage': 'complete', 'feature_preprocessor:feature_agglomeration:n_clusters': 276, 'feature_preprocessor:feature_agglomeration:pooling_func': 'max', 'regressor:gradient_boosting:early_stop': 'off', 'regressor:gradient_boosting:l2_regularization': 0.00018459550741867383, 'regressor:gradient_boosting:learning_rate': 0.04757728173371449, 'regressor:gradient_boosting:loss': 'least_squares', 'regressor:gradient_boosting:max_bins': 255, 'regressor:gradient_boosting:max_depth': 'None', 'regressor:gradient_boosting:max_leaf_nodes': 16, 'regressor:gradient_boosting:min_samples_leaf': 6, 'regressor:gradient_boosting:scoring': 'loss', 'regressor:gradient_boosting:tol': 1e-07}, + (0.160000, SimpleRegressionPipeline({'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'polynomial', 'regressor:__choice__': 'ard_regression', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'False', 'regressor:ard_regression:alpha_1': 0.0003701926442639788, 'regressor:ard_regression:alpha_2': 2.2118001735899097e-07, 'regressor:ard_regression:fit_intercept': 'True', 'regressor:ard_regression:lambda_1': 1.2037591637980971e-06, 'regressor:ard_regression:lambda_2': 4.358378124977852e-09, 'regressor:ard_regression:n_iter': 300, 'regressor:ard_regression:threshold_lambda': 1136.5286041327277, 'regressor:ard_regression:tol': 0.021944240404849075}, dataset_properties={ 'task': 4, 'sparse': False, @@ -73,7 +78,7 @@ The following example shows how to fit a simple regression model with 'target_type': 'regression', 'signed': False})), ] - R2 score: 0.8957471434869163 + R2 score: 0.9040477219435149 @@ -129,7 +134,7 @@ The following example shows how to fit a simple regression model with .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 2 minutes 4.422 seconds) + **Total running time of the script:** ( 1 minutes 57.803 seconds) .. _sphx_glr_download_examples_20_basic_example_regression.py: diff --git a/development/_sources/examples/20_basic/sg_execution_times.rst.txt b/development/_sources/examples/20_basic/sg_execution_times.rst.txt index 31ac1b6ab8..29847a20e2 100644 --- a/development/_sources/examples/20_basic/sg_execution_times.rst.txt +++ b/development/_sources/examples/20_basic/sg_execution_times.rst.txt @@ -5,12 +5,12 @@ Computation times ================= -**04:19.749** total execution time for **examples_20_basic** files: +**04:16.506** total execution time for **examples_20_basic** files: +-------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_20_basic_example_regression.py` (``example_regression.py``) | 02:04.422 | 0.0 MB | +| :ref:`sphx_glr_examples_20_basic_example_classification.py` (``example_classification.py``) | 01:59.910 | 0.0 MB | +-------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_20_basic_example_classification.py` (``example_classification.py``) | 01:55.477 | 0.0 MB | +| :ref:`sphx_glr_examples_20_basic_example_regression.py` (``example_regression.py``) | 01:57.803 | 0.0 MB | +-------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_20_basic_example_multilabel_classification.py` (``example_multilabel_classification.py``) | 00:19.850 | 0.0 MB | +| :ref:`sphx_glr_examples_20_basic_example_multilabel_classification.py` (``example_multilabel_classification.py``) | 00:18.793 | 0.0 MB | +-------------------------------------------------------------------------------------------------------------------+-----------+--------+ diff --git a/development/_sources/examples/40_advanced/example_feature_types.rst.txt b/development/_sources/examples/40_advanced/example_feature_types.rst.txt index 5500efe036..598a6d768b 100644 --- a/development/_sources/examples/40_advanced/example_feature_types.rst.txt +++ b/development/_sources/examples/40_advanced/example_feature_types.rst.txt @@ -93,7 +93,7 @@ types will be automatically inferred, as demonstrated in .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 15.510 seconds) + **Total running time of the script:** ( 0 minutes 15.363 seconds) .. _sphx_glr_download_examples_40_advanced_example_feature_types.py: diff --git a/development/_sources/examples/40_advanced/example_get_pipeline_components.rst.txt b/development/_sources/examples/40_advanced/example_get_pipeline_components.rst.txt index 8031f84685..9a86b0b907 100644 --- a/development/_sources/examples/40_advanced/example_get_pipeline_components.rst.txt +++ b/development/_sources/examples/40_advanced/example_get_pipeline_components.rst.txt @@ -32,138 +32,216 @@ with the sklearn components directly, in this case a PCA preprocessor. .. code-block:: none - [WARNING] [2020-12-11 17:37:55,306:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 15 not found - [WARNING] [2020-12-11 17:37:55,307:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 374 not found - 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17:37:55,325:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 346 not found - [WARNING] [2020-12-11 17:37:55,325:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 49 not found - [WARNING] [2020-12-11 17:37:55,326:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 435 not found - [WARNING] [2020-12-11 17:37:55,326:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 405 not found - [WARNING] [2020-12-11 17:37:55,326:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 462 not found - [WARNING] [2020-12-11 17:37:55,326:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 294 not found - [WARNING] [2020-12-11 17:37:55,326:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 450 not found - [WARNING] [2020-12-11 17:37:55,327:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 169 not found - [WARNING] [2020-12-11 17:37:55,327:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 415 not found - Accuracy score:0.9370629370629371 - [(0.280000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5422582251087723, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 17, 'classifier:random_forest:min_samples_split': 15, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0038512976944604285, 'feature_preprocessor:pca:keep_variance': 0.5735718374870298, 'feature_preprocessor:pca:whiten': 'False'}, + [WARNING] [2020-12-16 15:56:40,975:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 15:56:40,981:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:56:40,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 15:56:40,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 15:56:41,080:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 15:56:41,080:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 15:56:41,080:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:56:41,080:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [WARNING] [2020-12-16 15:56:41,081:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 176 not found + [WARNING] [2020-12-16 15:56:41,081:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found + [WARNING] 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15:56:41,110:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 322 not found + [WARNING] [2020-12-16 15:56:41,110:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 538 not found + [WARNING] [2020-12-16 15:56:41,110:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 86 not found + [WARNING] [2020-12-16 15:56:41,110:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 120 not found + [WARNING] [2020-12-16 15:56:41,110:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 452 not found + [WARNING] [2020-12-16 15:56:41,111:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 291 not found + [WARNING] [2020-12-16 15:56:41,111:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 102 not found + [WARNING] [2020-12-16 15:56:41,111:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 275 not found + [WARNING] [2020-12-16 15:56:41,111:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 150 not found + Accuracy score:0.951048951048951 + [(0.320000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.9331254454871041, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 20, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.005069923784737444, 'feature_preprocessor:pca:keep_variance': 0.9967857433838874, 'feature_preprocessor:pca:whiten': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -171,7 +249,7 @@ with the sklearn components directly, in this case a PCA preprocessor. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.260000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.006850480720592245, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 18, 'classifier:random_forest:min_samples_split': 19, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:pca:keep_variance': 0.5103852029213645, 'feature_preprocessor:pca:whiten': 'False'}, + (0.300000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'pca', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 1.103855734598575e-05, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.00014375616988222174, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 229, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.002766772136115771, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 180, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'uniform', 'feature_preprocessor:pca:keep_variance': 0.7895711479212801, 'feature_preprocessor:pca:whiten': 'True', 'classifier:mlp:validation_fraction': 0.1}, dataset_properties={ 'task': 1, 'sparse': False, @@ -179,7 +257,7 @@ with the sklearn components directly, in this case a PCA preprocessor. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.200000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01, 'feature_preprocessor:pca:keep_variance': 0.9999, 'feature_preprocessor:pca:whiten': 'False'}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01, 'feature_preprocessor:pca:keep_variance': 0.9999, 'feature_preprocessor:pca:whiten': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -187,7 +265,7 @@ with the sklearn components directly, in this case a PCA preprocessor. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'adaboost', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'pca', 'classifier:adaboost:algorithm': 'SAMME', 'classifier:adaboost:learning_rate': 0.011233995624432622, 'classifier:adaboost:max_depth': 9, 'classifier:adaboost:n_estimators': 477, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.018370622484682127, 'feature_preprocessor:pca:keep_variance': 0.6039710338898471, 'feature_preprocessor:pca:whiten': 'False'}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'libsvm_svc', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'pca', 'classifier:libsvm_svc:C': 100.5905006626969, 'classifier:libsvm_svc:gamma': 0.011333066835975528, 'classifier:libsvm_svc:kernel': 'poly', 'classifier:libsvm_svc:max_iter': -1, 'classifier:libsvm_svc:shrinking': 'True', 'classifier:libsvm_svc:tol': 0.012391313886912093, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010000000000000004, 'feature_preprocessor:pca:keep_variance': 0.9290439925152777, 'feature_preprocessor:pca:whiten': 'False', 'classifier:libsvm_svc:coef0': 0.08087614244138486, 'classifier:libsvm_svc:degree': 3}, dataset_properties={ 'task': 1, 'sparse': False, @@ -195,7 +273,7 @@ with the sklearn components directly, in this case a PCA preprocessor. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'adaboost', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'pca', 'classifier:adaboost:algorithm': 'SAMME', 'classifier:adaboost:learning_rate': 1.4120696722366737, 'classifier:adaboost:max_depth': 8, 'classifier:adaboost:n_estimators': 489, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.011307840322412704, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7357867136119712, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.2832469215827823, 'feature_preprocessor:pca:keep_variance': 0.99855313014133, 'feature_preprocessor:pca:whiten': 'True'}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'k_nearest_neighbors', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'pca', 'classifier:k_nearest_neighbors:n_neighbors': 4, 'classifier:k_nearest_neighbors:p': 2, 'classifier:k_nearest_neighbors:weights': 'distance', 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.008015420020402715, 'feature_preprocessor:pca:keep_variance': 0.8047274080856589, 'feature_preprocessor:pca:whiten': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -207,36 +285,39 @@ with the sklearn components directly, in this case a PCA preprocessor. auto-sklearn results: Dataset name: breast_cancer Metric: accuracy - Best validation score: 0.957447 - Number of target algorithm runs: 5 + Best validation score: 0.971631 + Number of target algorithm runs: 6 Number of successful target algorithm runs: 5 Number of crashed target algorithm runs: 0 - Number of target algorithms that exceeded the time limit: 0 + Number of target algorithms that exceeded the time limit: 1 Number of target algorithms that exceeded the memory limit: 0 - - 7 + + 8 ######### RunKey(config_id=1, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) - RunValue(cost=0.08510638297872342, time=2.528355360031128, status=, starttime=1607708276.0422819, endtime=1607708278.664568, additional_info={'duration': 1.6119797229766846, 'num_run': 2, 'train_loss': 0.0, 'configuration_origin': 'Initial design'}) + RunValue(cost=0.08510638297872342, time=2.608668565750122, status=, starttime=1608134201.9004984, endtime=1608134204.6039965, additional_info={'duration': 1.668154001235962, 'num_run': 2, 'train_loss': 0.0, 'configuration_origin': 'Initial design'}) ######### RunKey(config_id=2, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) - RunValue(cost=0.08510638297872342, time=1.0954289436340332, status=, starttime=1607708278.7016075, endtime=1607708279.8967123, additional_info={'duration': 0.24045133590698242, 'num_run': 3, 'train_loss': 0.0, 'configuration_origin': 'Initial design'}) + RunValue(cost=0.07092198581560283, time=2.3877782821655273, status=, starttime=1608134204.642403, endtime=1608134207.125843, additional_info={'duration': 1.3939154148101807, 'num_run': 3, 'train_loss': 0.06315789473684208, 'configuration_origin': 'Initial design'}) ######### RunKey(config_id=3, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) - RunValue(cost=0.04255319148936165, time=1.2550106048583984, status=, starttime=1607708281.8497431, endtime=1607708283.2112558, additional_info={'duration': 0.2447190284729004, 'num_run': 4, 'train_loss': 0.0, 'configuration_origin': 'Initial design'}) + RunValue(cost=0.028368794326241176, time=2.232430934906006, status=, starttime=1608134208.835775, endtime=1608134211.1629097, additional_info={'duration': 1.339444875717163, 'num_run': 4, 'train_loss': 0.04210526315789476, 'configuration_origin': 'Initial design'}) ######### RunKey(config_id=4, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) - RunValue(cost=0.06382978723404253, time=2.2705349922180176, status=, starttime=1607708283.5498817, endtime=1607708285.9264903, additional_info={'duration': 1.2342994213104248, 'num_run': 5, 'train_loss': 0.06666666666666665, 'configuration_origin': 'Random Search (sorted)'}) + RunValue(cost=0.1063829787234043, time=1.279904842376709, status=, starttime=1608134211.1975677, endtime=1608134212.5692801, additional_info={'duration': 0.35587143898010254, 'num_run': 5, 'train_loss': 0.0, 'configuration_origin': 'Initial design'}) ######### RunKey(config_id=5, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) - RunValue(cost=0.08510638297872342, time=2.6790971755981445, status=, starttime=1607708287.5379488, endtime=1607708290.322029, additional_info={'duration': 1.5631067752838135, 'num_run': 6, 'train_loss': 0.09824561403508769, 'configuration_origin': 'Random Search (sorted)'}) + RunValue(cost=0.11347517730496459, time=1.246011734008789, status=, starttime=1608134214.2991076, endtime=1608134215.6595075, additional_info={'duration': 0.2673919200897217, 'num_run': 6, 'train_loss': 0.09122807017543855, 'configuration_origin': 'Initial design'}) ######### RunKey(config_id=6, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) - RunValue(cost=2147483647.0, time=0.0, status=, starttime=0.0, endtime=0.0, additional_info=None) + RunValue(cost=1.0, time=1.0134475231170654, status=, starttime=1608134216.427164, endtime=1608134218.4495962, additional_info={'error': 'Timeout', 'configuration_origin': 'Random Search (sorted)'}) ######### RunKey(config_id=7, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) RunValue(cost=2147483647.0, time=0.0, status=, starttime=0.0, endtime=0.0, additional_info=None) + ######### + RunKey(config_id=8, instance_id='{"task_id": "breast_cancer"}', seed=0, budget=0.0) + RunValue(cost=2147483647.0, time=0.0, status=, starttime=0.0, endtime=0.0, additional_info=None) Configuration ID: 1 Instance: {"task_id": "breast_cancer"} Seed: 0 @@ -263,362 +344,368 @@ with the sklearn components directly, in this case a PCA preprocessor. feature_preprocessor:pca:whiten, Value: 'False' Cost: 0.08510638297872342 - Time: 2.528355360031128 + Time: 2.608668565750122 Status: StatusType.SUCCESS - Additional information: {'duration': 1.6119797229766846, 'num_run': 2, 'train_loss': 0.0, 'configuration_origin': 'Initial design'} - Start time: 1607708276.0422819 - End time 1607708278.664568 - Lowest loss: 0.04255319148936165 + Additional information: {'duration': 1.668154001235962, 'num_run': 2, 'train_loss': 0.0, 'configuration_origin': 'Initial design'} + Start time: 1608134201.9004984 + End time 1608134204.6039965 + Lowest loss: 0.028368794326241176 Best configuration: Configuration: - balancing:strategy, Value: 'none' - classifier:__choice__, Value: 'adaboost' - classifier:adaboost:algorithm, Value: 'SAMME' - classifier:adaboost:learning_rate, Value: 0.011233995624432622 - classifier:adaboost:max_depth, Value: 9 - classifier:adaboost:n_estimators, Value: 477 + balancing:strategy, Value: 'weighting' + classifier:__choice__, Value: 'mlp' + classifier:mlp:activation, Value: 'tanh' + classifier:mlp:alpha, Value: 1.103855734598575e-05 + classifier:mlp:batch_size, Constant: 'auto' + classifier:mlp:beta_1, Constant: 0.9 + classifier:mlp:beta_2, Constant: 0.999 + classifier:mlp:early_stopping, Value: 'valid' + classifier:mlp:epsilon, Constant: 1e-08 + classifier:mlp:hidden_layer_depth, Value: 3 + classifier:mlp:learning_rate_init, Value: 0.00014375616988222174 + classifier:mlp:n_iter_no_change, Constant: 32 + classifier:mlp:num_nodes_per_layer, Value: 229 + classifier:mlp:shuffle, Constant: 'True' + classifier:mlp:solver, Constant: 'adam' + classifier:mlp:tol, Constant: 0.0001 + classifier:mlp:validation_fraction, Constant: 0.1 data_preprocessing:categorical_transformer:categorical_encoding:__choice__, Value: 'no_encoding' data_preprocessing:categorical_transformer:category_coalescence:__choice__, Value: 'minority_coalescer' - data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction, Value: 0.018370622484682127 - data_preprocessing:numerical_transformer:imputation:strategy, Value: 'mean' - data_preprocessing:numerical_transformer:rescaling:__choice__, Value: 'standardize' + data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction, Value: 0.002766772136115771 + data_preprocessing:numerical_transformer:imputation:strategy, Value: 'most_frequent' + data_preprocessing:numerical_transformer:rescaling:__choice__, Value: 'quantile_transformer' + data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles, Value: 180 + data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution, Value: 'uniform' feature_preprocessor:__choice__, Value: 'pca' - feature_preprocessor:pca:keep_variance, Value: 0.6039710338898471 - feature_preprocessor:pca:whiten, Value: 'False' - - {'mean_test_score': array([0.91489362, 0.91489362, 0.95744681, 0.93617021, 0.91489362]), 'mean_fit_time': array([2.52835536, 1.09542894, 1.2550106 , 2.27053499, 2.67909718]), 'params': [{'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01, 'feature_preprocessor:pca:keep_variance': 0.9999, 'feature_preprocessor:pca:whiten': 'False'}, {'balancing:strategy': 'none', 'classifier:__choice__': 'adaboost', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'pca', 'classifier:adaboost:algorithm': 'SAMME', 'classifier:adaboost:learning_rate': 1.4120696722366737, 'classifier:adaboost:max_depth': 8, 'classifier:adaboost:n_estimators': 489, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.011307840322412704, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7357867136119712, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.2832469215827823, 'feature_preprocessor:pca:keep_variance': 0.99855313014133, 'feature_preprocessor:pca:whiten': 'True'}, {'balancing:strategy': 'none', 'classifier:__choice__': 'adaboost', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'pca', 'classifier:adaboost:algorithm': 'SAMME', 'classifier:adaboost:learning_rate': 0.011233995624432622, 'classifier:adaboost:max_depth': 9, 'classifier:adaboost:n_estimators': 477, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.018370622484682127, 'feature_preprocessor:pca:keep_variance': 0.6039710338898471, 'feature_preprocessor:pca:whiten': 'False'}, {'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5422582251087723, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 17, 'classifier:random_forest:min_samples_split': 15, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0038512976944604285, 'feature_preprocessor:pca:keep_variance': 0.5735718374870298, 'feature_preprocessor:pca:whiten': 'False'}, {'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.006850480720592245, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 18, 'classifier:random_forest:min_samples_split': 19, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:pca:keep_variance': 0.5103852029213645, 'feature_preprocessor:pca:whiten': 'False'}], 'rank_test_scores': array([3, 3, 1, 2, 3]), 'status': ['Success', 'Success', 'Success', 'Success', 'Success'], 'budgets': [0.0, 0.0, 0.0, 0.0, 0.0], 'param_balancing:strategy': masked_array(data=['none', 'none', 'none', 'none', 'weighting'], - mask=[False, False, False, False, False], + feature_preprocessor:pca:keep_variance, Value: 0.7895711479212801 + feature_preprocessor:pca:whiten, Value: 'True' + + {'mean_test_score': array([0.91489362, 0.92907801, 0.97163121, 0.89361702, 0.88652482, + 0. ]), 'mean_fit_time': array([2.60866857, 2.38777828, 2.23243093, 1.27990484, 1.24601173, + 1.01344752]), 'params': [{'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01, 'feature_preprocessor:pca:keep_variance': 0.9999, 'feature_preprocessor:pca:whiten': 'False'}, {'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.9331254454871041, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 20, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.005069923784737444, 'feature_preprocessor:pca:keep_variance': 0.9967857433838874, 'feature_preprocessor:pca:whiten': 'False'}, {'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'pca', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 1.103855734598575e-05, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.00014375616988222174, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 229, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.002766772136115771, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 180, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'uniform', 'feature_preprocessor:pca:keep_variance': 0.7895711479212801, 'feature_preprocessor:pca:whiten': 'True', 'classifier:mlp:validation_fraction': 0.1}, {'balancing:strategy': 'weighting', 'classifier:__choice__': 'k_nearest_neighbors', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'pca', 'classifier:k_nearest_neighbors:n_neighbors': 4, 'classifier:k_nearest_neighbors:p': 2, 'classifier:k_nearest_neighbors:weights': 'distance', 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.008015420020402715, 'feature_preprocessor:pca:keep_variance': 0.8047274080856589, 'feature_preprocessor:pca:whiten': 'False'}, {'balancing:strategy': 'none', 'classifier:__choice__': 'libsvm_svc', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'pca', 'classifier:libsvm_svc:C': 100.5905006626969, 'classifier:libsvm_svc:gamma': 0.011333066835975528, 'classifier:libsvm_svc:kernel': 'poly', 'classifier:libsvm_svc:max_iter': -1, 'classifier:libsvm_svc:shrinking': 'True', 'classifier:libsvm_svc:tol': 0.012391313886912093, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010000000000000004, 'feature_preprocessor:pca:keep_variance': 0.9290439925152777, 'feature_preprocessor:pca:whiten': 'False', 'classifier:libsvm_svc:coef0': 0.08087614244138486, 'classifier:libsvm_svc:degree': 3}, {'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'pca', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5422582251087723, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 17, 'classifier:random_forest:min_samples_split': 15, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0038512976944604285, 'feature_preprocessor:pca:keep_variance': 0.5735718374870298, 'feature_preprocessor:pca:whiten': 'False'}], 'rank_test_scores': array([3, 2, 1, 4, 5, 6]), 'status': ['Success', 'Success', 'Success', 'Success', 'Success', 'Timeout'], 'budgets': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 'param_balancing:strategy': masked_array(data=['none', 'none', 'weighting', 'weighting', 'none', + 'none'], + mask=[False, False, False, False, False, False], fill_value='N/A', - dtype=' + @@ -236,17 +236,25 @@ which means that it is automatically stopped one all computation is done. .. code-block:: none + [WARNING] [2020-12-16 16:01:03,787:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 16:01:03,793:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:01:03,796:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 16:01:03,805:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 16:01:03,891:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 16:01:03,892:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 16:01:03,892:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:01:03,892:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 auto-sklearn results: Dataset name: d6d58dae5b02e07797da6d4d126ac9b6 Metric: accuracy - Best validation score: 0.978723 - Number of target algorithm runs: 6 - Number of successful target algorithm runs: 3 + Best validation score: 0.985816 + Number of target algorithm runs: 8 + Number of successful target algorithm runs: 7 Number of crashed target algorithm runs: 0 - Number of target algorithms that exceeded the time limit: 2 - Number of target algorithms that exceeded the memory limit: 1 + Number of target algorithms that exceeded the time limit: 1 + Number of target algorithms that exceeded the memory limit: 0 - Accuracy score 0.9440559440559441 + Accuracy score 0.958041958041958 @@ -254,7 +262,7 @@ which means that it is automatically stopped one all computation is done. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 46.887 seconds) + **Total running time of the script:** ( 0 minutes 46.888 seconds) .. _sphx_glr_download_examples_60_search_example_parallel_manual_spawning.py: diff --git a/development/_sources/examples/60_search/example_parallel_n_jobs.rst.txt b/development/_sources/examples/60_search/example_parallel_n_jobs.rst.txt index 4d5d7fd7ad..13950d2bc2 100644 --- a/development/_sources/examples/60_search/example_parallel_n_jobs.rst.txt +++ b/development/_sources/examples/60_search/example_parallel_n_jobs.rst.txt @@ -94,14 +94,22 @@ To use ``n_jobs_`` we must guard the code .. code-block:: none + [WARNING] [2020-12-16 15:57:08,481:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 15:57:08,487:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:57:08,491:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 15:57:08,501:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 15:57:08,592:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 15:57:08,592:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 15:57:08,593:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:57:08,593:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 auto-sklearn results: Dataset name: breast_cancer Metric: accuracy - Best validation score: 0.978723 - Number of target algorithm runs: 24 - Number of successful target algorithm runs: 14 - Number of crashed target algorithm runs: 1 - Number of target algorithms that exceeded the time limit: 9 + Best validation score: 0.985816 + Number of target algorithm runs: 31 + Number of successful target algorithm runs: 28 + Number of crashed target algorithm runs: 2 + Number of target algorithms that exceeded the time limit: 1 Number of target algorithms that exceeded the memory limit: 0 @@ -111,7 +119,7 @@ To use ``n_jobs_`` we must guard the code .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 1 minutes 55.531 seconds) + **Total running time of the script:** ( 1 minutes 59.308 seconds) .. _sphx_glr_download_examples_60_search_example_parallel_n_jobs.py: diff --git a/development/_sources/examples/60_search/example_random_search.rst.txt b/development/_sources/examples/60_search/example_random_search.rst.txt index fef55e2a86..3066f1bdc8 100644 --- a/development/_sources/examples/60_search/example_random_search.rst.txt +++ b/development/_sources/examples/60_search/example_random_search.rst.txt @@ -446,7 +446,7 @@ Both examples are intended to show how the optimization strategy in *auto-sklear .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 1 minutes 46.024 seconds) + **Total running time of the script:** ( 1 minutes 47.307 seconds) .. _sphx_glr_download_examples_60_search_example_random_search.py: diff --git a/development/_sources/examples/60_search/example_sequential.rst.txt b/development/_sources/examples/60_search/example_sequential.rst.txt index 447cbe8032..8d0e0355b6 100644 --- a/development/_sources/examples/60_search/example_sequential.rst.txt +++ b/development/_sources/examples/60_search/example_sequential.rst.txt @@ -27,7 +27,15 @@ ensembles afterwards. .. code-block:: none - [(0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.7304811343030777, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 3, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7202654714984674, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.21555973677200435, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'average', 'feature_preprocessor:feature_agglomeration:n_clusters': 149, 'feature_preprocessor:feature_agglomeration:pooling_func': 'median'}, + [WARNING] [2020-12-16 15:59:05,967:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 15:59:05,973:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:59:05,976:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 15:59:05,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 15:59:06,074:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 15:59:06,074:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 15:59:06,074:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 15:59:06,074:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [(0.160000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5707983257382487, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 3, 'classifier:extra_trees:min_samples_split': 11, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -35,7 +43,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'lda', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:lda:shrinkage': 'auto', 'classifier:lda:tol': 0.00225057974134912, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.021216521648541566, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'ward', 'feature_preprocessor:feature_agglomeration:n_clusters': 43, 'feature_preprocessor:feature_agglomeration:pooling_func': 'mean'}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'bernoulli_nb', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'nystroem_sampler', 'classifier:bernoulli_nb:alpha': 0.027571829114140422, 'classifier:bernoulli_nb:fit_prior': 'False', 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.12674505954687995, 'feature_preprocessor:nystroem_sampler:kernel': 'rbf', 'feature_preprocessor:nystroem_sampler:n_components': 75, 'feature_preprocessor:nystroem_sampler:gamma': 3.7450381067167084}, dataset_properties={ 'task': 1, 'sparse': False, @@ -43,7 +51,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 10, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1000, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'True'}, + (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:passive_aggressive:C': 0.14268277711454813, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.0002600768160857831, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0070580904199417415}, dataset_properties={ 'task': 1, 'sparse': False, @@ -51,7 +59,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 8.495727973549814e-08, 'classifier:gradient_boosting:learning_rate': 0.10895774269386836, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 17, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.009766287299931831, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 917, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False', 'classifier:gradient_boosting:n_iter_no_change': 16, 'classifier:gradient_boosting:validation_fraction': 0.018763788815745606}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'kernel_pca', 'classifier:passive_aggressive:C': 0.06780321808789821, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.000882998841830217, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1828, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:kernel_pca:kernel': 'cosine', 'feature_preprocessor:kernel_pca:n_components': 561}, dataset_properties={ 'task': 1, 'sparse': False, @@ -59,7 +67,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'liblinear_svc', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:liblinear_svc:C': 1.0, 'classifier:liblinear_svc:dual': 'False', 'classifier:liblinear_svc:fit_intercept': 'True', 'classifier:liblinear_svc:intercept_scaling': 1, 'classifier:liblinear_svc:loss': 'squared_hinge', 'classifier:liblinear_svc:multi_class': 'ovr', 'classifier:liblinear_svc:penalty': 'l2', 'classifier:liblinear_svc:tol': 2.858526169098402e-05, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0007827505640681123, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.3443310459451119, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 3, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'lda', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'pca', 'classifier:lda:shrinkage': 'auto', 'classifier:lda:tol': 0.0006344726053453868, 'feature_preprocessor:pca:keep_variance': 0.7348293443711987, 'feature_preprocessor:pca:whiten': 'True'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -67,7 +75,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.1697146122414465, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010046143955337466}, + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 1.0647401999412075e-10, 'classifier:gradient_boosting:learning_rate': 0.08291320147381159, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 39, 'classifier:gradient_boosting:min_samples_leaf': 20, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.008520698757932555, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7710965306105907, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.257333974790539, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'ward', 'feature_preprocessor:feature_agglomeration:n_clusters': 25, 'feature_preprocessor:feature_agglomeration:pooling_func': 'max'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -75,7 +83,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.9346290154944297, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 17, 'classifier:extra_trees:min_samples_split': 12, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.00012944629495230338, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.9759954818316919, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.257981682107215, 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'True'}, + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 2.5550223982458062e-06, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'train', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.00027271287919467994, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 54, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.017116661677715188, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.7171678618990129, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 4, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 17, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -83,7 +91,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 1.944632809484799e-07, 'classifier:gradient_boosting:learning_rate': 0.06023679587502036, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 28, 'classifier:gradient_boosting:min_samples_leaf': 193, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False', 'classifier:gradient_boosting:n_iter_no_change': 15, 'classifier:gradient_boosting:validation_fraction': 0.0639715328873465}, + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 8.057778875694463e-05, 'classifier:gradient_boosting:learning_rate': 0.09179220974965213, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 200, 'classifier:gradient_boosting:min_samples_leaf': 20, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.008542188583124829, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1102, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'uniform', 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'gini', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.9984367650965825, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 13, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 18, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100, 'classifier:gradient_boosting:n_iter_no_change': 18, 'classifier:gradient_boosting:validation_fraction': 0.14295295806077554}, dataset_properties={ 'task': 1, 'sparse': False, @@ -91,7 +99,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'gaussian_nb', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'fast_ica', 'feature_preprocessor:fast_ica:algorithm': 'deflation', 'feature_preprocessor:fast_ica:fun': 'cube', 'feature_preprocessor:fast_ica:whiten': 'False'}, + (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:passive_aggressive:C': 0.0011715712307920933, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.0028863384989190936, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'True', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'gini', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.13274693159200124, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 14, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 8, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -99,7 +107,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'qda', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:qda:reg_param': 0.563056219822946, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.32793677336996485}, + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'select_percentile_classification', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 3.387912939529945e-10, 'classifier:gradient_boosting:learning_rate': 0.30755227194768237, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 60, 'classifier:gradient_boosting:min_samples_leaf': 39, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010000000000000004, 'feature_preprocessor:select_percentile_classification:percentile': 93.39844669585806, 'feature_preprocessor:select_percentile_classification:score_func': 'f_classif', 'classifier:gradient_boosting:n_iter_no_change': 18}, dataset_properties={ 'task': 1, 'sparse': False, @@ -107,7 +115,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 0.00022373024203887573, 'classifier:gradient_boosting:learning_rate': 0.027149343206135476, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 49, 'classifier:gradient_boosting:min_samples_leaf': 13, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.00777614320416325, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, dataset_properties={ 'task': 1, 'sparse': False, @@ -115,7 +123,7 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.21772092350860472, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 14, 'classifier:random_forest:min_samples_split': 17, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0020488212891693275, 'feature_preprocessor:liblinear_svc_preprocessor:C': 33.74257606530722, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 8.740452966205111e-05}, + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.43999367631975456, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'True', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.8134515743047006, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 9, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 20, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -123,7 +131,79 @@ ensembles afterwards. 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 0.0006322356877253852, 'classifier:gradient_boosting:learning_rate': 0.02155479872417127, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 15, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'select_percentile_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 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'feature_preprocessor:feature_agglomeration:n_clusters': 182, 'feature_preprocessor:feature_agglomeration:pooling_func': 'mean', 'classifier:mlp:validation_fraction': 0.1}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 0.005326508887463406, 'classifier:gradient_boosting:learning_rate': 0.060800813211425456, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 5, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:liblinear_svc_preprocessor:C': 13.550960330919455, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 1.2958033930435781e-05, 'classifier:gradient_boosting:n_iter_no_change': 5}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 0.4635442279519353, 'classifier:gradient_boosting:learning_rate': 0.09809681787962342, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 328, 'classifier:gradient_boosting:min_samples_leaf': 2, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0208475757765491, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.989729761503726, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 19, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 5, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100, 'classifier:gradient_boosting:n_iter_no_change': 2}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5805882119281688, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.11533421526707399, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'gini', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.8490063449951434, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 9, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.9292309396985746, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 1, 'classifier:extra_trees:min_samples_split': 10, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.032719158639429445, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.9929881254946676, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'fast_ica', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 0.00022912929717932768, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.0008758720949591471, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 229, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:fast_ica:algorithm': 'deflation', 'feature_preprocessor:fast_ica:fun': 'exp', 'feature_preprocessor:fast_ica:whiten': 'True', 'classifier:mlp:validation_fraction': 0.1, 'feature_preprocessor:fast_ica:n_components': 1791}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'bernoulli_nb', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'fast_ica', 'classifier:bernoulli_nb:alpha': 0.010361094658759605, 'classifier:bernoulli_nb:fit_prior': 'False', 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.27580741838616984, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.8765822498756136, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.09937717217884853, 'feature_preprocessor:fast_ica:algorithm': 'deflation', 'feature_preprocessor:fast_ica:fun': 'exp', 'feature_preprocessor:fast_ica:whiten': 'False'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'qda', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:qda:reg_param': 0.9414401592303469, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0013185563485050603, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'True'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'k_nearest_neighbors', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:k_nearest_neighbors:n_neighbors': 100, 'classifier:k_nearest_neighbors:p': 2, 'classifier:k_nearest_neighbors:weights': 'distance', 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1925, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -135,14 +215,14 @@ ensembles afterwards. auto-sklearn results: Dataset name: breast_cancer Metric: accuracy - Best validation score: 0.992908 - Number of target algorithm runs: 18 - Number of successful target algorithm runs: 16 + Best validation score: 0.985816 + Number of target algorithm runs: 34 + Number of successful target algorithm runs: 34 Number of crashed target algorithm runs: 0 - Number of target algorithms that exceeded the time limit: 2 + Number of target algorithms that exceeded the time limit: 0 Number of target algorithms that exceeded the memory limit: 0 - Accuracy score 0.958041958041958 + Accuracy score 0.9440559440559441 @@ -209,7 +289,7 @@ ensembles afterwards. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 1 minutes 56.107 seconds) + **Total running time of the script:** ( 1 minutes 56.597 seconds) .. _sphx_glr_download_examples_60_search_example_sequential.py: diff --git a/development/_sources/examples/60_search/example_successive_halving.rst.txt b/development/_sources/examples/60_search/example_successive_halving.rst.txt index d4b3bbc391..b361e386cd 100644 --- a/development/_sources/examples/60_search/example_successive_halving.rst.txt +++ b/development/_sources/examples/60_search/example_successive_halving.rst.txt @@ -28,126 +28,202 @@ the intensification strategy to use in smac, in this case: .. code-block:: none - [WARNING] [2020-12-11 17:44:43,753:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 15 not found - [WARNING] [2020-12-11 17:44:43,754:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 374 not found - [WARNING] [2020-12-11 17:44:43,754:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 301 not found - [WARNING] [2020-12-11 17:44:43,754:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 114 not found - [WARNING] [2020-12-11 17:44:43,754:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 321 not found - [WARNING] [2020-12-11 17:44:43,754:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 179 not found - [WARNING] 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17:44:43,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 200 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 58 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 63 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 237 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 13 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 99 not found - [WARNING] [2020-12-11 17:44:43,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 342 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 96 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 388 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 422 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 35 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 11 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 317 not found - [WARNING] [2020-12-11 17:44:43,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 212 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 311 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 55 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 408 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 3 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 105 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 304 not found - [WARNING] [2020-12-11 17:44:43,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 458 not found - [WARNING] [2020-12-11 17:44:43,774:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 352 not found - [WARNING] [2020-12-11 17:44:43,774:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 222 not found - [WARNING] [2020-12-11 17:44:43,774:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 111 not found - [WARNING] [2020-12-11 17:44:43,774:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 175 not found - [WARNING] [2020-12-11 17:44:43,774:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 346 not found - [WARNING] [2020-12-11 17:44:43,775:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 49 not found - [WARNING] [2020-12-11 17:44:43,775:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 435 not found - [WARNING] [2020-12-11 17:44:43,775:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 405 not found - [WARNING] [2020-12-11 17:44:43,775:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 462 not found - [WARNING] [2020-12-11 17:44:43,775:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 294 not found - [WARNING] [2020-12-11 17:44:43,775:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 450 not found - [WARNING] [2020-12-11 17:44:43,776:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 169 not found + [WARNING] [2020-12-16 16:03:38,063:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 16:03:38,070:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:03:38,075:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 16:03:38,085:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 16:03:38,174:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 16:03:38,174:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 176 not found + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 476 not found + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 601 not found + [WARNING] [2020-12-16 16:03:38,175:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 492 not found + [WARNING] [2020-12-16 16:03:38,176:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 440 not found + [WARNING] [2020-12-16 16:03:38,176:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 32 not found + [WARNING] [2020-12-16 16:03:38,176:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 220 not found + [WARNING] [2020-12-16 16:03:38,176:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 332 not found + [WARNING] [2020-12-16 16:03:38,176:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 22 not found + [WARNING] [2020-12-16 16:03:38,176:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 61 not found + [WARNING] [2020-12-16 16:03:38,177:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 407 not found + [WARNING] [2020-12-16 16:03:38,177:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 91 not found + [WARNING] [2020-12-16 16:03:38,177:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 702 not found + [WARNING] [2020-12-16 16:03:38,177:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 546 not found + [WARNING] [2020-12-16 16:03:38,177:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 663 not found + [WARNING] [2020-12-16 16:03:38,178:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 257 not found + [WARNING] [2020-12-16 16:03:38,178:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 631 not found + [WARNING] [2020-12-16 16:03:38,178:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 7 not found + [WARNING] [2020-12-16 16:03:38,178:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 184 not found + [WARNING] [2020-12-16 16:03:38,179:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 560 not found + [WARNING] [2020-12-16 16:03:38,179:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 329 not found + [WARNING] [2020-12-16 16:03:38,179:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 386 not found + [WARNING] [2020-12-16 16:03:38,179:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 9 not found + [WARNING] [2020-12-16 16:03:38,179:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 345 not found + [WARNING] [2020-12-16 16:03:38,180:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 399 not found + [WARNING] [2020-12-16 16:03:38,180:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 222 not found + [WARNING] [2020-12-16 16:03:38,180:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 149 not found + [WARNING] [2020-12-16 16:03:38,180:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 238 not found + [WARNING] [2020-12-16 16:03:38,180:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 211 not found + [WARNING] [2020-12-16 16:03:38,180:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 358 not found + [WARNING] [2020-12-16 16:03:38,181:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 188 not found + [WARNING] [2020-12-16 16:03:38,181:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 460 not found + [WARNING] [2020-12-16 16:03:38,181:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 585 not found + [WARNING] [2020-12-16 16:03:38,181:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 690 not found + [WARNING] [2020-12-16 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16:03:38,184:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 347 not found + [WARNING] [2020-12-16 16:03:38,184:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 701 not found + [WARNING] [2020-12-16 16:03:38,185:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 266 not found + [WARNING] [2020-12-16 16:03:38,185:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 28 not found + [WARNING] [2020-12-16 16:03:38,185:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 282 not found + [WARNING] [2020-12-16 16:03:38,185:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 367 not found + [WARNING] [2020-12-16 16:03:38,185:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 518 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 648 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 67 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 521 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 227 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 145 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 576 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 680 not found + [WARNING] [2020-12-16 16:03:38,186:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 605 not found + [WARNING] [2020-12-16 16:03:38,187:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 624 not found + [WARNING] [2020-12-16 16:03:38,187:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 191 not found + [WARNING] [2020-12-16 16:03:38,187:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 414 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 574 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 283 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 262 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 369 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 444 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 264 not found + [WARNING] [2020-12-16 16:03:38,188:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 14 not found + [WARNING] [2020-12-16 16:03:38,189:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 430 not found + [WARNING] [2020-12-16 16:03:38,190:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 674 not found + [WARNING] [2020-12-16 16:03:38,190:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 563 not found + [WARNING] [2020-12-16 16:03:38,190:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 357 not found + [WARNING] [2020-12-16 16:03:38,190:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 338 not found + [WARNING] [2020-12-16 16:03:38,190:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 43 not found + [WARNING] [2020-12-16 16:03:38,191:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 160 not found + [WARNING] [2020-12-16 16:03:38,191:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 382 not found + [WARNING] [2020-12-16 16:03:38,191:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 53 not found + [WARNING] [2020-12-16 16:03:38,191:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 48 not found + [WARNING] [2020-12-16 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16:03:38,207:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 452 not found + [WARNING] [2020-12-16 16:03:38,207:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 291 not found + [WARNING] [2020-12-16 16:03:38,207:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 275 not found /opt/hostedtoolcache/Python/3.8.6/x64/lib/python3.8/site-packages/smac/intensification/parallel_scheduling.py:149: UserWarning: SuccessiveHalving is intended to be used with more than 1 worker but num_workers=1 warnings.warn("{} is intended to be used " - [(0.180000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.1697146122414465, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010046143955337466}, + [(0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.6128603428070196, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 1, 'classifier:extra_trees:min_samples_split': 3, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.08125391652261632, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.8601586365248128, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.052862156055921525}, dataset_properties={ 'task': 1, 'sparse': False, @@ -155,7 +231,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.180000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.6473984346629116, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 13, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.013705109439767781}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'sgd', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:sgd:alpha': 0.0002346515712987664, 'classifier:sgd:average': 'True', 'classifier:sgd:fit_intercept': 'True', 'classifier:sgd:learning_rate': 'optimal', 'classifier:sgd:loss': 'log', 'classifier:sgd:penalty': 'l1', 'classifier:sgd:tol': 1.3716748930467322e-05}, dataset_properties={ 'task': 1, 'sparse': False, @@ -163,7 +239,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 3.79982070767762e-10, 'classifier:gradient_boosting:learning_rate': 0.10307173798074214, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 30, 'classifier:gradient_boosting:min_samples_leaf': 25, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.004889186641013006, 'classifier:gradient_boosting:n_iter_no_change': 6, 'classifier:gradient_boosting:validation_fraction': 0.09705336338563596}, + (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.41808321658160696, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 4, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.011283688651384545}, dataset_properties={ 'task': 1, 'sparse': False, @@ -171,7 +247,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 6.090138036399552e-10, 'classifier:gradient_boosting:learning_rate': 0.017305568433437588, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 202, 'classifier:gradient_boosting:min_samples_leaf': 188, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7526196011313747, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.1563616005702636}, + (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 1e-10, 'classifier:gradient_boosting:learning_rate': 0.16262682406125173, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 66, 'classifier:gradient_boosting:min_samples_leaf': 20, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.005428587241449129, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.75, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.23746960178084334}, dataset_properties={ 'task': 1, 'sparse': False, @@ -179,7 +255,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.9441835876839625, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 3, 'classifier:random_forest:min_samples_split': 15, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 696, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal'}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.41808321658160696, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 4, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.011283688651384545}, dataset_properties={ 'task': 1, 'sparse': False, @@ -187,7 +263,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 3.79982070767762e-10, 'classifier:gradient_boosting:learning_rate': 0.10307173798074214, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 30, 'classifier:gradient_boosting:min_samples_leaf': 25, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.004889186641013006, 'classifier:gradient_boosting:n_iter_no_change': 6, 'classifier:gradient_boosting:validation_fraction': 0.09705336338563596}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.926283631486858, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 7, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.16265262021972576}, dataset_properties={ 'task': 1, 'sparse': False, @@ -195,7 +271,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 3.609412172481434e-10, 'classifier:gradient_boosting:learning_rate': 0.05972079854295879, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 4, 'classifier:gradient_boosting:min_samples_leaf': 2, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'classifier:gradient_boosting:n_iter_no_change': 14}, dataset_properties={ 'task': 1, 'sparse': False, @@ -211,7 +287,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.1697146122414465, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010046143955337466}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, dataset_properties={ 'task': 1, 'sparse': False, @@ -219,7 +295,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5033866291997137, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 14, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.6128603428070196, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 1, 'classifier:extra_trees:min_samples_split': 3, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.08125391652261632, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.8601586365248128, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.052862156055921525}, dataset_properties={ 'task': 1, 'sparse': False, @@ -227,7 +303,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 6.611729692973355e-06, 'classifier:gradient_boosting:learning_rate': 0.057217701969255366, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 8, 'classifier:gradient_boosting:min_samples_leaf': 1, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:passive_aggressive:C': 0.14268277711454813, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.0002600768160857831, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0070580904199417415}, dataset_properties={ 'task': 1, 'sparse': False, @@ -239,134 +315,218 @@ the intensification strategy to use in smac, in this case: auto-sklearn results: Dataset name: breast_cancer Metric: accuracy - Best validation score: 0.992908 + Best validation score: 0.985816 Number of target algorithm runs: 11 Number of successful target algorithm runs: 11 Number of crashed target algorithm runs: 0 Number of target algorithms that exceeded the time limit: 0 Number of target algorithms that exceeded the memory limit: 0 - Accuracy score 0.958041958041958 - [WARNING] [2020-12-11 17:45:16,497:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 15 not found - [WARNING] [2020-12-11 17:45:16,497:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 374 not found - [WARNING] [2020-12-11 17:45:16,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 301 not found - [WARNING] [2020-12-11 17:45:16,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 114 not found - [WARNING] [2020-12-11 17:45:16,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 321 not found - [WARNING] [2020-12-11 17:45:16,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 179 not found - [WARNING] [2020-12-11 17:45:16,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] 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17:45:16,509:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 208 not found - [WARNING] [2020-12-11 17:45:16,509:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 428 not found - [WARNING] [2020-12-11 17:45:16,510:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 290 not found - [WARNING] [2020-12-11 17:45:16,510:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 246 not found - [WARNING] [2020-12-11 17:45:16,510:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 369 not found - [WARNING] [2020-12-11 17:45:16,510:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 320 not found - [WARNING] [2020-12-11 17:45:16,511:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found - [WARNING] [2020-12-11 17:45:16,511:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 200 not found - [WARNING] [2020-12-11 17:45:16,511:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 58 not found - [WARNING] [2020-12-11 17:45:16,511:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 63 not found - [WARNING] [2020-12-11 17:45:16,511:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 237 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 13 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 99 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 342 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 96 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 388 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 422 not found - [WARNING] [2020-12-11 17:45:16,512:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 35 not found - [WARNING] [2020-12-11 17:45:16,513:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 11 not found - [WARNING] [2020-12-11 17:45:16,513:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 317 not found - [WARNING] [2020-12-11 17:45:16,513:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 212 not found - [WARNING] [2020-12-11 17:45:16,513:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 311 not found - [WARNING] [2020-12-11 17:45:16,513:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 55 not found - [WARNING] [2020-12-11 17:45:16,514:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 408 not found - [WARNING] [2020-12-11 17:45:16,514:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 3 not found - [WARNING] [2020-12-11 17:45:16,514:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 105 not found - [WARNING] [2020-12-11 17:45:16,514:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 304 not found - [WARNING] [2020-12-11 17:45:16,514:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 458 not found - [WARNING] [2020-12-11 17:45:16,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 352 not found - [WARNING] [2020-12-11 17:45:16,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 222 not found - [WARNING] [2020-12-11 17:45:16,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 111 not found - [WARNING] [2020-12-11 17:45:16,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 175 not found - [WARNING] [2020-12-11 17:45:16,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 346 not found - [WARNING] [2020-12-11 17:45:16,515:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 49 not found - [WARNING] [2020-12-11 17:45:16,516:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 435 not found - [WARNING] [2020-12-11 17:45:16,516:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 405 not found - [WARNING] [2020-12-11 17:45:16,516:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 462 not found - [WARNING] [2020-12-11 17:45:16,517:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 294 not found - [WARNING] [2020-12-11 17:45:16,517:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 450 not found - [WARNING] [2020-12-11 17:45:16,517:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 169 not found + Accuracy score 0.951048951048951 + [WARNING] [2020-12-16 16:04:10,648:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 16:04:10,656:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:04:10,660:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 16:04:10,672:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 16:04:10,756:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 16:04:10,756:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 176 not found + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 476 not found + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 601 not found + [WARNING] [2020-12-16 16:04:10,757:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 492 not found + [WARNING] [2020-12-16 16:04:10,758:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 440 not found + [WARNING] [2020-12-16 16:04:10,758:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 32 not found + [WARNING] [2020-12-16 16:04:10,758:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 220 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 332 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 22 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 61 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 407 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 91 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 702 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 546 not found + [WARNING] [2020-12-16 16:04:10,759:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 663 not found + [WARNING] [2020-12-16 16:04:10,760:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 257 not found + [WARNING] [2020-12-16 16:04:10,760:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 631 not found + [WARNING] [2020-12-16 16:04:10,760:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 7 not found + [WARNING] [2020-12-16 16:04:10,760:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 184 not found + [WARNING] [2020-12-16 16:04:10,760:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 560 not found + [WARNING] [2020-12-16 16:04:10,760:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 329 not found + [WARNING] [2020-12-16 16:04:10,761:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 386 not found + [WARNING] [2020-12-16 16:04:10,761:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 9 not found + [WARNING] [2020-12-16 16:04:10,761:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 345 not found + [WARNING] [2020-12-16 16:04:10,761:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 399 not found + [WARNING] [2020-12-16 16:04:10,762:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 222 not found + [WARNING] [2020-12-16 16:04:10,762:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 149 not found + [WARNING] [2020-12-16 16:04:10,762:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 238 not found + [WARNING] [2020-12-16 16:04:10,762:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 211 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 358 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 188 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 460 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 585 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 690 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 254 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 473 not found + [WARNING] [2020-12-16 16:04:10,763:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 71 not found + [WARNING] [2020-12-16 16:04:10,764:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 230 not found + [WARNING] [2020-12-16 16:04:10,764:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 108 not found + [WARNING] [2020-12-16 16:04:10,764:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 590 not found + [WARNING] [2020-12-16 16:04:10,764:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 81 not found + [WARNING] [2020-12-16 16:04:10,764:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 506 not found + [WARNING] [2020-12-16 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16:04:10,767:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 701 not found + [WARNING] [2020-12-16 16:04:10,767:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 266 not found + [WARNING] [2020-12-16 16:04:10,767:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 28 not found + [WARNING] [2020-12-16 16:04:10,767:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 282 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 367 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 518 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 648 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 67 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 521 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 227 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 145 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 576 not found + [WARNING] [2020-12-16 16:04:10,768:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 680 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 605 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 624 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 191 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 414 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 574 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 283 not found + [WARNING] [2020-12-16 16:04:10,769:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 262 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 369 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 444 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 264 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 14 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 430 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 674 not found + [WARNING] [2020-12-16 16:04:10,770:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 563 not found + [WARNING] [2020-12-16 16:04:10,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 357 not found + [WARNING] [2020-12-16 16:04:10,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 338 not found + [WARNING] [2020-12-16 16:04:10,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 43 not found + [WARNING] [2020-12-16 16:04:10,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 160 not found + [WARNING] [2020-12-16 16:04:10,771:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 382 not found + [WARNING] [2020-12-16 16:04:10,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 53 not found + [WARNING] [2020-12-16 16:04:10,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 48 not found + [WARNING] [2020-12-16 16:04:10,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 536 not found + [WARNING] [2020-12-16 16:04:10,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 555 not found + [WARNING] [2020-12-16 16:04:10,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 214 not found + [WARNING] [2020-12-16 16:04:10,772:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 388 not found + [WARNING] [2020-12-16 16:04:10,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 676 not found + [WARNING] [2020-12-16 16:04:10,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 97 not found + [WARNING] [2020-12-16 16:04:10,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 40 not found + [WARNING] [2020-12-16 16:04:10,773:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 270 not found + [WARNING] [2020-12-16 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16:04:10,788:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 291 not found + [WARNING] [2020-12-16 16:04:10,788:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 275 not found /opt/hostedtoolcache/Python/3.8.6/x64/lib/python3.8/site-packages/smac/intensification/parallel_scheduling.py:149: UserWarning: SuccessiveHalving is intended to be used with more than 1 worker but num_workers=1 warnings.warn("{} is intended to be used " - [(0.580000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.1697146122414465, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010046143955337466}, + [(0.240000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'sgd', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:sgd:alpha': 0.0002346515712987664, 'classifier:sgd:average': 'True', 'classifier:sgd:fit_intercept': 'True', 'classifier:sgd:learning_rate': 'optimal', 'classifier:sgd:loss': 'log', 'classifier:sgd:penalty': 'l1', 'classifier:sgd:tol': 1.3716748930467322e-05}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.200000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:passive_aggressive:C': 0.14268277711454813, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.0002600768160857831, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0070580904199417415}, dataset_properties={ 'task': 1, 'sparse': False, @@ -374,7 +534,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.180000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + (0.180000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.41808321658160696, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 4, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.011283688651384545}, dataset_properties={ 'task': 1, 'sparse': False, @@ -382,7 +542,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 6.090138036399552e-10, 'classifier:gradient_boosting:learning_rate': 0.017305568433437588, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 202, 'classifier:gradient_boosting:min_samples_leaf': 188, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7526196011313747, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.1563616005702636}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.926283631486858, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 7, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.16265262021972576}, dataset_properties={ 'task': 1, 'sparse': False, @@ -390,7 +550,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 6.611729692973355e-06, 'classifier:gradient_boosting:learning_rate': 0.057217701969255366, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 8, 'classifier:gradient_boosting:min_samples_leaf': 1, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, dataset_properties={ 'task': 1, 'sparse': False, @@ -398,7 +558,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5033866291997137, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 14, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 1e-10, 'classifier:gradient_boosting:learning_rate': 0.16262682406125173, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 66, 'classifier:gradient_boosting:min_samples_leaf': 20, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.005428587241449129, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.75, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.23746960178084334}, dataset_properties={ 'task': 1, 'sparse': False, @@ -406,7 +566,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.6473984346629116, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 13, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.013705109439767781}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 3.609412172481434e-10, 'classifier:gradient_boosting:learning_rate': 0.05972079854295879, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 4, 'classifier:gradient_boosting:min_samples_leaf': 2, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'classifier:gradient_boosting:n_iter_no_change': 14}, dataset_properties={ 'task': 1, 'sparse': False, @@ -418,134 +578,210 @@ the intensification strategy to use in smac, in this case: auto-sklearn results: Dataset name: breast_cancer Metric: accuracy - Best validation score: 0.962441 + Best validation score: 0.964789 Number of target algorithm runs: 7 Number of successful target algorithm runs: 7 Number of crashed target algorithm runs: 0 Number of target algorithms that exceeded the time limit: 0 Number of target algorithms that exceeded the memory limit: 0 - Accuracy score 0.951048951048951 - [WARNING] [2020-12-11 17:45:50,042:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 15 not found - [WARNING] [2020-12-11 17:45:50,042:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 374 not found - [WARNING] [2020-12-11 17:45:50,042:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 301 not found - [WARNING] [2020-12-11 17:45:50,042:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 114 not found - [WARNING] [2020-12-11 17:45:50,042:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 321 not found - [WARNING] [2020-12-11 17:45:50,043:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 179 not found - [WARNING] [2020-12-11 17:45:50,043:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 91 not found - [WARNING] [2020-12-11 17:45:50,043:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 165 not found - [WARNING] [2020-12-11 17:45:50,043:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 29 not found - [WARNING] [2020-12-11 17:45:50,043:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 23 not found - [WARNING] [2020-12-11 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17:45:50,061:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 175 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 346 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 49 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 435 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 405 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 462 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 294 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 450 not found - [WARNING] [2020-12-11 17:45:50,062:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 169 not found + Accuracy score 0.965034965034965 + [WARNING] [2020-12-16 16:04:44,877:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 16:04:44,882:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:04:44,886:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 16:04:44,895:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 16:04:44,980:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 176 not found + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 476 not found + [WARNING] [2020-12-16 16:04:44,981:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 601 not found + [WARNING] [2020-12-16 16:04:44,982:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 492 not found + [WARNING] [2020-12-16 16:04:44,982:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 440 not found + [WARNING] [2020-12-16 16:04:44,982:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 32 not found + [WARNING] [2020-12-16 16:04:44,982:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 220 not found + [WARNING] [2020-12-16 16:04:44,982:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 332 not found + [WARNING] [2020-12-16 16:04:44,982:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 22 not found + [WARNING] [2020-12-16 16:04:44,983:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 61 not found + [WARNING] [2020-12-16 16:04:44,983:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 407 not found + [WARNING] [2020-12-16 16:04:44,983:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 91 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 702 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 546 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 663 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 257 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 631 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 7 not found + [WARNING] [2020-12-16 16:04:44,984:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 184 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 560 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 329 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 386 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 9 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 345 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 399 not found + [WARNING] [2020-12-16 16:04:44,985:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 222 not found + [WARNING] [2020-12-16 16:04:44,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 149 not found + [WARNING] [2020-12-16 16:04:44,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 238 not found + [WARNING] [2020-12-16 16:04:44,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 211 not found + [WARNING] [2020-12-16 16:04:44,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 358 not found + [WARNING] [2020-12-16 16:04:44,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 188 not found + [WARNING] [2020-12-16 16:04:44,986:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 460 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 585 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 690 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 254 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 473 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 71 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 230 not found + [WARNING] [2020-12-16 16:04:44,987:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 108 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 590 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 81 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 506 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 694 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 426 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 327 not found + [WARNING] [2020-12-16 16:04:44,988:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 657 not found + [WARNING] [2020-12-16 16:04:44,989:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 532 not found + [WARNING] [2020-12-16 16:04:44,989:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 315 not found + [WARNING] [2020-12-16 16:04:44,989:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 138 not found + [WARNING] [2020-12-16 16:04:44,989:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 206 not found + [WARNING] [2020-12-16 16:04:44,989:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 579 not found + [WARNING] [2020-12-16 16:04:44,989:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 454 not found + [WARNING] [2020-12-16 16:04:44,990:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 1 not found + [WARNING] [2020-12-16 16:04:44,990:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 147 not found + [WARNING] [2020-12-16 16:04:44,990:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 393 not found + [WARNING] [2020-12-16 16:04:44,990:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 347 not found + [WARNING] [2020-12-16 16:04:44,990:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 701 not found + [WARNING] [2020-12-16 16:04:44,990:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 266 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 28 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 282 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 367 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 518 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 648 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 67 not found + [WARNING] [2020-12-16 16:04:44,991:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 521 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 227 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 145 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 576 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 680 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 605 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 624 not found + [WARNING] [2020-12-16 16:04:44,992:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 191 not found + [WARNING] [2020-12-16 16:04:44,993:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 414 not found + [WARNING] [2020-12-16 16:04:44,993:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 574 not found + [WARNING] [2020-12-16 16:04:44,993:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 283 not found + [WARNING] [2020-12-16 16:04:44,993:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 262 not found + [WARNING] [2020-12-16 16:04:44,994:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 369 not found + [WARNING] [2020-12-16 16:04:44,994:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 444 not found + [WARNING] [2020-12-16 16:04:44,994:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 264 not found + [WARNING] [2020-12-16 16:04:44,994:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 14 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 430 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 674 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 563 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 357 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 338 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 43 not found + [WARNING] [2020-12-16 16:04:44,995:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 160 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 382 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 53 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 48 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 536 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 555 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 214 not found + [WARNING] [2020-12-16 16:04:44,996:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 388 not found + [WARNING] [2020-12-16 16:04:44,997:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 676 not found + [WARNING] [2020-12-16 16:04:44,997:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 97 not found + [WARNING] [2020-12-16 16:04:44,997:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 40 not found + [WARNING] [2020-12-16 16:04:44,997:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 270 not found + [WARNING] [2020-12-16 16:04:44,997:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 512 not found + [WARNING] [2020-12-16 16:04:44,998:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 595 not found + [WARNING] [2020-12-16 16:04:44,998:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 131 not found + [WARNING] [2020-12-16 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16:04:45,002:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 99 not found + [WARNING] [2020-12-16 16:04:45,002:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 434 not found + [WARNING] [2020-12-16 16:04:45,002:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 494 not found + [WARNING] [2020-12-16 16:04:45,003:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 615 not found + [WARNING] [2020-12-16 16:04:45,003:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 587 not found + [WARNING] [2020-12-16 16:04:45,003:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 302 not found + [WARNING] [2020-12-16 16:04:45,003:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 653 not found + [WARNING] [2020-12-16 16:04:45,003:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 445 not found + [WARNING] [2020-12-16 16:04:45,004:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 69 not found + [WARNING] [2020-12-16 16:04:45,004:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 437 not found + [WARNING] [2020-12-16 16:04:45,004:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 142 not found + [WARNING] [2020-12-16 16:04:45,004:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 310 not found + [WARNING] [2020-12-16 16:04:45,004:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 173 not found + [WARNING] [2020-12-16 16:04:45,004:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 647 not found + [WARNING] [2020-12-16 16:04:45,005:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 461 not found + [WARNING] [2020-12-16 16:04:45,005:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 515 not found + [WARNING] [2020-12-16 16:04:45,005:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 17 not found + [WARNING] [2020-12-16 16:04:45,005:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 395 not found + [WARNING] [2020-12-16 16:04:45,005:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 25 not found + [WARNING] [2020-12-16 16:04:45,005:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 56 not found + [WARNING] [2020-12-16 16:04:45,006:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 121 not found + [WARNING] [2020-12-16 16:04:45,006:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 165 not found + [WARNING] [2020-12-16 16:04:45,006:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 313 not found + [WARNING] [2020-12-16 16:04:45,006:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 412 not found + [WARNING] [2020-12-16 16:04:45,007:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 288 not found + [WARNING] [2020-12-16 16:04:45,007:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 298 not found + [WARNING] [2020-12-16 16:04:45,007:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 486 not found + [WARNING] [2020-12-16 16:04:45,008:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 243 not found + [WARNING] [2020-12-16 16:04:45,008:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 480 not found + [WARNING] [2020-12-16 16:04:45,008:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 553 not found + [WARNING] [2020-12-16 16:04:45,008:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 363 not found + [WARNING] [2020-12-16 16:04:45,008:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 528 not found + [WARNING] [2020-12-16 16:04:45,008:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 403 not found + [WARNING] [2020-12-16 16:04:45,009:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 622 not found + [WARNING] [2020-12-16 16:04:45,009:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 448 not found + [WARNING] [2020-12-16 16:04:45,009:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 543 not found + [WARNING] [2020-12-16 16:04:45,010:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 548 not found + [WARNING] [2020-12-16 16:04:45,010:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 499 not found + [WARNING] [2020-12-16 16:04:45,010:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 171 not found + [WARNING] [2020-12-16 16:04:45,011:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 19 not found + [WARNING] [2020-12-16 16:04:45,011:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 58 not found + [WARNING] [2020-12-16 16:04:45,011:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 640 not found + [WARNING] [2020-12-16 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16:04:45,012:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 538 not found + [WARNING] [2020-12-16 16:04:45,012:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 86 not found + [WARNING] [2020-12-16 16:04:45,012:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 120 not found + [WARNING] [2020-12-16 16:04:45,012:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 452 not found + [WARNING] [2020-12-16 16:04:45,012:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 291 not found + [WARNING] [2020-12-16 16:04:45,013:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 275 not found /opt/hostedtoolcache/Python/3.8.6/x64/lib/python3.8/site-packages/smac/intensification/parallel_scheduling.py:149: UserWarning: SuccessiveHalving is intended to be used with more than 1 worker but num_workers=1 warnings.warn("{} is intended to be used " - [(0.320000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.1697146122414465, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.010046143955337466}, + [(0.300000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 1e-10, 'classifier:gradient_boosting:learning_rate': 0.16262682406125173, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 66, 'classifier:gradient_boosting:min_samples_leaf': 20, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.005428587241449129, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.75, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.23746960178084334}, dataset_properties={ 'task': 1, 'sparse': False, @@ -553,7 +789,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.240000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 6.611729692973355e-06, 'classifier:gradient_boosting:learning_rate': 0.057217701969255366, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 8, 'classifier:gradient_boosting:min_samples_leaf': 1, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07}, + (0.280000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, dataset_properties={ 'task': 1, 'sparse': False, @@ -561,7 +797,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.200000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + (0.240000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'passive_aggressive', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:passive_aggressive:C': 0.14268277711454813, 'classifier:passive_aggressive:average': 'False', 'classifier:passive_aggressive:fit_intercept': 'True', 'classifier:passive_aggressive:loss': 'hinge', 'classifier:passive_aggressive:tol': 0.0002600768160857831, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0070580904199417415}, dataset_properties={ 'task': 1, 'sparse': False, @@ -569,7 +805,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.160000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 6.090138036399552e-10, 'classifier:gradient_boosting:learning_rate': 0.017305568433437588, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 202, 'classifier:gradient_boosting:min_samples_leaf': 188, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7526196011313747, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.1563616005702636}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.926283631486858, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 7, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.16265262021972576}, dataset_properties={ 'task': 1, 'sparse': False, @@ -577,7 +813,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5033866291997137, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 14, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 3.609412172481434e-10, 'classifier:gradient_boosting:learning_rate': 0.05972079854295879, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 4, 'classifier:gradient_boosting:min_samples_leaf': 2, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'classifier:gradient_boosting:n_iter_no_change': 14}, dataset_properties={ 'task': 1, 'sparse': False, @@ -589,7 +825,7 @@ the intensification strategy to use in smac, in this case: auto-sklearn results: Dataset name: breast_cancer Metric: accuracy - Best validation score: 0.962441 + Best validation score: 0.964789 Number of target algorithm runs: 5 Number of successful target algorithm runs: 5 Number of crashed target algorithm runs: 0 @@ -597,9 +833,41 @@ the intensification strategy to use in smac, in this case: Number of target algorithms that exceeded the memory limit: 0 Accuracy score 0.958041958041958 + [WARNING] [2020-12-16 16:05:19,779:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 16:05:19,785:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:05:19,788:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 16:05:19,798:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 16:05:19,881:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 16:05:19,881:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 16:05:19,882:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:05:19,882:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 /opt/hostedtoolcache/Python/3.8.6/x64/lib/python3.8/site-packages/smac/intensification/parallel_scheduling.py:149: UserWarning: SuccessiveHalving is intended to be used with more than 1 worker but num_workers=1 warnings.warn("{} is intended to be used " - [(0.340000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + [(0.180000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 0.0001363185819149026, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.00018009776276177523, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 115, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'ward', 'feature_preprocessor:feature_agglomeration:n_clusters': 182, 'feature_preprocessor:feature_agglomeration:pooling_func': 'mean', 'classifier:mlp:validation_fraction': 0.1}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.180000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'fast_ica', 'classifier:mlp:activation': 'relu', 'classifier:mlp:alpha': 0.0017940473175767063, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'valid', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 2, 'classifier:mlp:learning_rate_init': 0.0004684917334431039, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 101, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:fast_ica:algorithm': 'parallel', 'feature_preprocessor:fast_ica:fun': 'exp', 'feature_preprocessor:fast_ica:whiten': 'False', 'classifier:mlp:validation_fraction': 0.1}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.4775492074518431, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.015996368052062886, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7845396961078424, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.25545052141264185, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.5662900693317384, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 7, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -607,7 +875,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.260000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.7304811343030777, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 3, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7202654714984674, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.21555973677200435, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'average', 'feature_preprocessor:feature_agglomeration:n_clusters': 149, 'feature_preprocessor:feature_agglomeration:pooling_func': 'median'}, + (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.9292309396985746, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 1, 'classifier:extra_trees:min_samples_split': 10, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.032719158639429445, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.9929881254946676, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -615,7 +883,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.240000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.21772092350860472, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 14, 'classifier:random_forest:min_samples_split': 17, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0020488212891693275, 'feature_preprocessor:liblinear_svc_preprocessor:C': 33.74257606530722, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 8.740452966205111e-05}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'mlp', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:mlp:activation': 'tanh', 'classifier:mlp:alpha': 0.00021148999718383549, 'classifier:mlp:batch_size': 'auto', 'classifier:mlp:beta_1': 0.9, 'classifier:mlp:beta_2': 0.999, 'classifier:mlp:early_stopping': 'train', 'classifier:mlp:epsilon': 1e-08, 'classifier:mlp:hidden_layer_depth': 3, 'classifier:mlp:learning_rate_init': 0.0007452270241186694, 'classifier:mlp:n_iter_no_change': 32, 'classifier:mlp:num_nodes_per_layer': 113, 'classifier:mlp:shuffle': 'True', 'classifier:mlp:solver': 'adam', 'classifier:mlp:tol': 0.0001, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'complete', 'feature_preprocessor:feature_agglomeration:n_clusters': 247, 'feature_preprocessor:feature_agglomeration:pooling_func': 'max'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -623,7 +891,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.120000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 0.0001694678378411361, 'classifier:gradient_boosting:learning_rate': 0.02193023008887291, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 20, 'classifier:gradient_boosting:min_samples_leaf': 25, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.43999367631975456, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'True', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.8134515743047006, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 9, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 20, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -631,7 +899,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.040000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 8.495727973549814e-08, 'classifier:gradient_boosting:learning_rate': 0.10895774269386836, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 17, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.009766287299931831, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 917, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False', 'classifier:gradient_boosting:n_iter_no_change': 16, 'classifier:gradient_boosting:validation_fraction': 0.018763788815745606}, + (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5707983257382487, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 3, 'classifier:extra_trees:min_samples_split': 11, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -644,61 +912,131 @@ the intensification strategy to use in smac, in this case: Dataset name: breast_cancer Metric: accuracy Best validation score: 0.978723 - Number of target algorithm runs: 6 - Number of successful target algorithm runs: 5 + Number of target algorithm runs: 8 + Number of successful target algorithm runs: 8 Number of crashed target algorithm runs: 0 - Number of target algorithms that exceeded the time limit: 1 + Number of target algorithms that exceeded the time limit: 0 Number of target algorithms that exceeded the memory limit: 0 - Accuracy score 0.916083916083916 - [WARNING] [2020-12-11 17:46:56,070:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 114 not found - [WARNING] [2020-12-11 17:46:56,071:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 165 not found - [WARNING] [2020-12-11 17:46:56,071:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 29 not found - [WARNING] [2020-12-11 17:46:56,072:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 44 not found - [WARNING] [2020-12-11 17:46:56,072:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 68 not found - [WARNING] [2020-12-11 17:46:56,072:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 267 not found - [WARNING] [2020-12-11 17:46:56,073:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 1 not found - [WARNING] [2020-12-11 17:46:56,073:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 328 not found - [WARNING] [2020-12-11 17:46:56,074:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 110 not found - [WARNING] [2020-12-11 17:46:56,075:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 298 not found - [WARNING] [2020-12-11 17:46:56,076:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 219 not found - [WARNING] [2020-12-11 17:46:56,076:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 362 not found - [WARNING] [2020-12-11 17:46:56,077:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 139 not found - [WARNING] [2020-12-11 17:46:56,080:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 392 not found - [WARNING] [2020-12-11 17:46:56,081:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 337 not found - [WARNING] [2020-12-11 17:46:56,081:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 322 not found - [WARNING] [2020-12-11 17:46:56,081:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 286 not found - [WARNING] [2020-12-11 17:46:56,081:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 335 not found - [WARNING] [2020-12-11 17:46:56,082:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 445 not found - [WARNING] [2020-12-11 17:46:56,082:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 233 not found - [WARNING] [2020-12-11 17:46:56,082:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 8 not found - [WARNING] [2020-12-11 17:46:56,082:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 187 not found - [WARNING] [2020-12-11 17:46:56,082:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 116 not found - [WARNING] [2020-12-11 17:46:56,083:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 225 not found - [WARNING] [2020-12-11 17:46:56,083:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 403 not found - [WARNING] [2020-12-11 17:46:56,083:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 75 not found - [WARNING] [2020-12-11 17:46:56,083:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 146 not found - [WARNING] [2020-12-11 17:46:56,083:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 213 not found - [WARNING] [2020-12-11 17:46:56,083:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 32 not found - [WARNING] [2020-12-11 17:46:56,084:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 215 not found - [WARNING] [2020-12-11 17:46:56,085:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 290 not found - [WARNING] [2020-12-11 17:46:56,085:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 246 not found - [WARNING] [2020-12-11 17:46:56,085:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 320 not found - [WARNING] [2020-12-11 17:46:56,086:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 63 not found - [WARNING] [2020-12-11 17:46:56,086:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 13 not found - [WARNING] [2020-12-11 17:46:56,087:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 99 not found - [WARNING] [2020-12-11 17:46:56,087:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 388 not found - [WARNING] [2020-12-11 17:46:56,087:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 35 not found - [WARNING] [2020-12-11 17:46:56,087:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 11 not found - [WARNING] [2020-12-11 17:46:56,088:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 212 not found - [WARNING] [2020-12-11 17:46:56,088:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 311 not found - [WARNING] [2020-12-11 17:46:56,088:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 408 not found - [WARNING] [2020-12-11 17:46:56,089:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 304 not found - [WARNING] [2020-12-11 17:46:56,091:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 405 not found - [WARNING] [2020-12-11 17:46:56,091:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 462 not found + Accuracy score 0.9440559440559441 + [WARNING] [2020-12-16 16:05:52,350:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10 + [WARNING] [2020-12-16 16:05:52,357:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:05:52,361:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49 + [WARNING] [2020-12-16 16:05:52,371:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn + [WARNING] [2020-12-16 16:05:52,461:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10 + [WARNING] [2020-12-16 16:05:52,462:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn + [WARNING] [2020-12-16 16:05:52,462:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03 + [WARNING] [2020-12-16 16:05:52,462:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49 + [WARNING] [2020-12-16 16:05:52,462:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 176 not found + [WARNING] [2020-12-16 16:05:52,462:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 162 not found + [WARNING] [2020-12-16 16:05:52,463:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 601 not found + [WARNING] [2020-12-16 16:05:52,464:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 22 not found + [WARNING] [2020-12-16 16:05:52,465:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 407 not 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16:05:52,497:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 452 not found + [WARNING] [2020-12-16 16:05:52,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 291 not found + [WARNING] [2020-12-16 16:05:52,498:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Configuration 150 not found /opt/hostedtoolcache/Python/3.8.6/x64/lib/python3.8/site-packages/smac/intensification/parallel_scheduling.py:149: UserWarning: SuccessiveHalving is intended to be used with more than 1 worker but num_workers=1 warnings.warn("{} is intended to be used " - [(0.540000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'valid', 'classifier:gradient_boosting:l2_regularization': 8.495727973549814e-08, 'classifier:gradient_boosting:learning_rate': 0.10895774269386836, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 17, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.009766287299931831, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 917, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False', 'classifier:gradient_boosting:n_iter_no_change': 16, 'classifier:gradient_boosting:validation_fraction': 0.018763788815745606}, + [(0.260000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5707983257382487, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 3, 'classifier:extra_trees:min_samples_split': 11, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.220000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'none', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.5707983257382487, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 3, 'classifier:extra_trees:min_samples_split': 11, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'False', 'feature_preprocessor:polynomial:interaction_only': 'False'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -706,7 +1044,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.260000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 0.005326508887463406, 'classifier:gradient_boosting:learning_rate': 0.060800813211425456, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 5, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:liblinear_svc_preprocessor:C': 13.550960330919455, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 1.2958033930435781e-05, 'classifier:gradient_boosting:n_iter_no_change': 5}, dataset_properties={ 'task': 1, 'sparse': False, @@ -714,7 +1052,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'liblinear_svc_preprocessor', 'classifier:random_forest:bootstrap': 'False', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.21772092350860472, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 14, 'classifier:random_forest:min_samples_split': 17, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.0020488212891693275, 'feature_preprocessor:liblinear_svc_preprocessor:C': 33.74257606530722, 'feature_preprocessor:liblinear_svc_preprocessor:dual': 'False', 'feature_preprocessor:liblinear_svc_preprocessor:fit_intercept': 'True', 'feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling': 1, 'feature_preprocessor:liblinear_svc_preprocessor:loss': 'squared_hinge', 'feature_preprocessor:liblinear_svc_preprocessor:multi_class': 'ovr', 'feature_preprocessor:liblinear_svc_preprocessor:penalty': 'l1', 'feature_preprocessor:liblinear_svc_preprocessor:tol': 8.740452966205111e-05}, + (0.140000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.43999367631975456, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'True', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.8134515743047006, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 9, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 20, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -722,7 +1060,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.060000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'feature_agglomeration', 'classifier:extra_trees:bootstrap': 'True', 'classifier:extra_trees:criterion': 'entropy', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.7304811343030777, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 2, 'classifier:extra_trees:min_samples_split': 3, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7202654714984674, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.21555973677200435, 'feature_preprocessor:feature_agglomeration:affinity': 'euclidean', 'feature_preprocessor:feature_agglomeration:linkage': 'average', 'feature_preprocessor:feature_agglomeration:n_clusters': 149, 'feature_preprocessor:feature_agglomeration:pooling_func': 'median'}, + (0.100000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'extra_trees', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'normalize', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:extra_trees:bootstrap': 'False', 'classifier:extra_trees:criterion': 'gini', 'classifier:extra_trees:max_depth': 'None', 'classifier:extra_trees:max_features': 0.9292309396985746, 'classifier:extra_trees:max_leaf_nodes': 'None', 'classifier:extra_trees:min_impurity_decrease': 0.0, 'classifier:extra_trees:min_samples_leaf': 1, 'classifier:extra_trees:min_samples_split': 10, 'classifier:extra_trees:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.032719158639429445, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.9929881254946676, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 2, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, dataset_properties={ 'task': 1, 'sparse': False, @@ -730,7 +1068,7 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'median', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'quantile_transformer', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 10, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:n_quantiles': 1000, 'data_preprocessing:numerical_transformer:rescaling:quantile_transformer:output_distribution': 'normal', 'feature_preprocessor:polynomial:degree': 3, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'True'}, + (0.080000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, dataset_properties={ 'task': 1, 'sparse': False, @@ -738,7 +1076,23 @@ the intensification strategy to use in smac, in this case: 'multiclass': False, 'target_type': 'classification', 'signed': False})), - (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'polynomial', 'classifier:gradient_boosting:early_stop': 'off', 'classifier:gradient_boosting:l2_regularization': 0.0006322356877253852, 'classifier:gradient_boosting:learning_rate': 0.02155479872417127, 'classifier:gradient_boosting:loss': 'auto', 'classifier:gradient_boosting:max_bins': 255, 'classifier:gradient_boosting:max_depth': 'None', 'classifier:gradient_boosting:max_leaf_nodes': 6, 'classifier:gradient_boosting:min_samples_leaf': 15, 'classifier:gradient_boosting:scoring': 'loss', 'classifier:gradient_boosting:tol': 1e-07, 'feature_preprocessor:polynomial:degree': 2, 'feature_preprocessor:polynomial:include_bias': 'True', 'feature_preprocessor:polynomial:interaction_only': 'False'}, + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'none', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'mean', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'standardize', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'gini', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.5, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.01}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'robust_scaler', 'feature_preprocessor:__choice__': 'extra_trees_preproc_for_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.4775492074518431, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 2, 'classifier:random_forest:min_samples_split': 2, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.015996368052062886, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_max': 0.7845396961078424, 'data_preprocessing:numerical_transformer:rescaling:robust_scaler:q_min': 0.25545052141264185, 'feature_preprocessor:extra_trees_preproc_for_classification:bootstrap': 'False', 'feature_preprocessor:extra_trees_preproc_for_classification:criterion': 'entropy', 'feature_preprocessor:extra_trees_preproc_for_classification:max_depth': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:max_features': 0.5662900693317384, 'feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes': 'None', 'feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf': 1, 'feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split': 7, 'feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf': 0.0, 'feature_preprocessor:extra_trees_preproc_for_classification:n_estimators': 100}, + dataset_properties={ + 'task': 1, + 'sparse': False, + 'multilabel': False, + 'multiclass': False, + 'target_type': 'classification', + 'signed': False})), + (0.020000, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'random_forest', 'data_preprocessing:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessing:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessing:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessing:numerical_transformer:rescaling:__choice__': 'minmax', 'feature_preprocessor:__choice__': 'select_percentile_classification', 'classifier:random_forest:bootstrap': 'True', 'classifier:random_forest:criterion': 'entropy', 'classifier:random_forest:max_depth': 'None', 'classifier:random_forest:max_features': 0.49138075723513286, 'classifier:random_forest:max_leaf_nodes': 'None', 'classifier:random_forest:min_impurity_decrease': 0.0, 'classifier:random_forest:min_samples_leaf': 1, 'classifier:random_forest:min_samples_split': 6, 'classifier:random_forest:min_weight_fraction_leaf': 0.0, 'data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.42693600390988135, 'feature_preprocessor:select_percentile_classification:percentile': 56.97947373958566, 'feature_preprocessor:select_percentile_classification:score_func': 'mutual_info'}, dataset_properties={ 'task': 1, 'sparse': False, @@ -751,13 +1105,13 @@ the intensification strategy to use in smac, in this case: Dataset name: breast_cancer Metric: accuracy Best validation score: 0.985816 - Number of target algorithm runs: 9 - Number of successful target algorithm runs: 8 + Number of target algorithm runs: 11 + Number of successful target algorithm runs: 10 Number of crashed target algorithm runs: 0 Number of target algorithms that exceeded the time limit: 1 Number of target algorithms that exceeded the memory limit: 0 - Accuracy score 0.951048951048951 + Accuracy score 0.9440559440559441 @@ -999,7 +1353,7 @@ the intensification strategy to use in smac, in this case: .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 2 minutes 46.384 seconds) + **Total running time of the script:** ( 2 minutes 47.604 seconds) .. _sphx_glr_download_examples_60_search_example_successive_halving.py: diff --git a/development/_sources/examples/60_search/sg_execution_times.rst.txt b/development/_sources/examples/60_search/sg_execution_times.rst.txt index 1b7dac60b7..e8bc957d4d 100644 --- a/development/_sources/examples/60_search/sg_execution_times.rst.txt +++ b/development/_sources/examples/60_search/sg_execution_times.rst.txt @@ -5,16 +5,16 @@ Computation times ================= -**09:10.932** total execution time for **examples_60_search** files: +**09:17.703** total execution time for **examples_60_search** files: +------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_60_search_example_successive_halving.py` (``example_successive_halving.py``) | 02:46.384 | 0.0 MB | +| :ref:`sphx_glr_examples_60_search_example_successive_halving.py` (``example_successive_halving.py``) | 02:47.604 | 0.0 MB | +------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_60_search_example_sequential.py` (``example_sequential.py``) | 01:56.107 | 0.0 MB | +| :ref:`sphx_glr_examples_60_search_example_parallel_n_jobs.py` (``example_parallel_n_jobs.py``) | 01:59.308 | 0.0 MB | +------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_60_search_example_parallel_n_jobs.py` (``example_parallel_n_jobs.py``) | 01:55.531 | 0.0 MB | +| :ref:`sphx_glr_examples_60_search_example_sequential.py` (``example_sequential.py``) | 01:56.597 | 0.0 MB | +------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_60_search_example_random_search.py` (``example_random_search.py``) | 01:46.024 | 0.0 MB | +| :ref:`sphx_glr_examples_60_search_example_random_search.py` (``example_random_search.py``) | 01:47.307 | 0.0 MB | +------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_60_search_example_parallel_manual_spawning.py` (``example_parallel_manual_spawning.py``) | 00:46.887 | 0.0 MB | +| :ref:`sphx_glr_examples_60_search_example_parallel_manual_spawning.py` (``example_parallel_manual_spawning.py``) | 00:46.888 | 0.0 MB | +------------------------------------------------------------------------------------------------------------------+-----------+--------+ diff --git a/development/_sources/examples/80_extending/example_extending_classification.rst.txt b/development/_sources/examples/80_extending/example_extending_classification.rst.txt index 1ac0d7c994..55c5cd24ac 100644 --- a/development/_sources/examples/80_extending/example_extending_classification.rst.txt +++ b/development/_sources/examples/80_extending/example_extending_classification.rst.txt @@ -191,7 +191,7 @@ Create MLP classifier component for auto-sklearn num_nodes_per_layer, Type: UniformInteger, Range: [16, 216], Default: 32 solver, Type: Categorical, Choices: {lbfgs, sgd, adam}, Default: adam - accuracy: 0.3356643356643357 + accuracy: 0.40559440559440557 [(1.000000, MyDummyClassifier(configuration=1, init_params={'instance': None}, random_state=1)), ] @@ -202,7 +202,7 @@ Create MLP classifier component for auto-sklearn .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 15.963 seconds) + **Total running time of the script:** ( 0 minutes 15.163 seconds) .. _sphx_glr_download_examples_80_extending_example_extending_classification.py: diff --git a/development/_sources/examples/80_extending/example_extending_preprocessor.rst.txt b/development/_sources/examples/80_extending/example_extending_preprocessor.rst.txt index 7ed8e07403..ae07721c3e 100644 --- a/development/_sources/examples/80_extending/example_extending_preprocessor.rst.txt +++ b/development/_sources/examples/80_extending/example_extending_preprocessor.rst.txt @@ -171,7 +171,7 @@ Create LDA component for auto-sklearn Conditions: shrinkage | solver in {'lsqr', 'eigen'} - accuracy: 0.3706293706293706 + accuracy: 0.3916083916083916 [(1.000000, MyDummyClassifier(configuration=1, init_params={'instance': None}, random_state=1)), ] @@ -182,7 +182,7 @@ Create LDA component for auto-sklearn .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 17.910 seconds) + **Total running time of the script:** ( 0 minutes 17.971 seconds) .. _sphx_glr_download_examples_80_extending_example_extending_preprocessor.py: diff --git a/development/_sources/examples/80_extending/example_extending_regression.rst.txt b/development/_sources/examples/80_extending/example_extending_regression.rst.txt index 671eb17f4a..592ffea40d 100644 --- a/development/_sources/examples/80_extending/example_extending_regression.rst.txt +++ b/development/_sources/examples/80_extending/example_extending_regression.rst.txt @@ -189,7 +189,7 @@ Implement kernel ridge regression component for auto-sklearn .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 15.317 seconds) + **Total running time of the script:** ( 0 minutes 15.298 seconds) .. _sphx_glr_download_examples_80_extending_example_extending_regression.py: diff --git a/development/_sources/examples/80_extending/example_restrict_number_of_hyperparameters.rst.txt b/development/_sources/examples/80_extending/example_restrict_number_of_hyperparameters.rst.txt index 1e1e111011..2e88824cd1 100644 --- a/development/_sources/examples/80_extending/example_restrict_number_of_hyperparameters.rst.txt +++ b/development/_sources/examples/80_extending/example_restrict_number_of_hyperparameters.rst.txt @@ -546,7 +546,7 @@ but with different hyperparameters . .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 8.159 seconds) + **Total running time of the script:** ( 0 minutes 7.846 seconds) .. _sphx_glr_download_examples_80_extending_example_restrict_number_of_hyperparameters.py: diff --git a/development/_sources/examples/80_extending/sg_execution_times.rst.txt b/development/_sources/examples/80_extending/sg_execution_times.rst.txt index 4e17171a99..b63afe3550 100644 --- a/development/_sources/examples/80_extending/sg_execution_times.rst.txt +++ b/development/_sources/examples/80_extending/sg_execution_times.rst.txt @@ -5,14 +5,14 @@ Computation times ================= -**00:57.349** total execution time for **examples_80_extending** files: +**00:56.278** total execution time for **examples_80_extending** files: +-----------------------------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_80_extending_example_extending_preprocessor.py` (``example_extending_preprocessor.py``) | 00:17.910 | 0.0 MB | +| :ref:`sphx_glr_examples_80_extending_example_extending_preprocessor.py` (``example_extending_preprocessor.py``) | 00:17.971 | 0.0 MB | +-----------------------------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_80_extending_example_extending_classification.py` (``example_extending_classification.py``) | 00:15.963 | 0.0 MB | +| :ref:`sphx_glr_examples_80_extending_example_extending_regression.py` (``example_extending_regression.py``) | 00:15.298 | 0.0 MB | +-----------------------------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_80_extending_example_extending_regression.py` (``example_extending_regression.py``) | 00:15.317 | 0.0 MB | +| :ref:`sphx_glr_examples_80_extending_example_extending_classification.py` (``example_extending_classification.py``) | 00:15.163 | 0.0 MB | +-----------------------------------------------------------------------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_80_extending_example_restrict_number_of_hyperparameters.py` (``example_restrict_number_of_hyperparameters.py``) | 00:08.159 | 0.0 MB | +| :ref:`sphx_glr_examples_80_extending_example_restrict_number_of_hyperparameters.py` (``example_restrict_number_of_hyperparameters.py``) | 00:07.846 | 0.0 MB | +-----------------------------------------------------------------------------------------------------------------------------------------+-----------+--------+ diff --git a/development/examples/20_basic/example_classification.html b/development/examples/20_basic/example_classification.html index c9bffb2fb9..30f4f74ef4 100644 --- a/development/examples/20_basic/example_classification.html +++ b/development/examples/20_basic/example_classification.html @@ -121,7 +121,15 @@

The following example shows how to fit a simple classification model with auto-sklearn.

Out:

-
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+
[WARNING] [2020-12-16 15:41:21,210:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance cifar_10
+[WARNING] [2020-12-16 15:41:21,216:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance gtsrb-hog03
+[WARNING] [2020-12-16 15:41:21,219:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance kuzushiji-49
+[WARNING] [2020-12-16 15:41:21,229:autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner] Could not find runs for instance svhn
+[WARNING] [2020-12-16 15:41:21,317:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance cifar_10
+[WARNING] [2020-12-16 15:41:21,318:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance svhn
+[WARNING] [2020-12-16 15:41:21,318:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance gtsrb-hog03
+[WARNING] [2020-12-16 15:41:21,318:autosklearn.metalearning.metalearning.kNearestDatasets.kND] Found no best configuration for instance kuzushiji-49
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@@ -129,7 +137,7 @@
   'multiclass': False,
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@@ -137,7 +145,7 @@
   'multiclass': False,
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@@ -145,7 +153,7 @@
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@@ -153,7 +161,7 @@
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@@ -161,7 +169,7 @@
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@@ -169,7 +177,7 @@
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@@ -177,7 +185,7 @@
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@@ -185,7 +193,103 @@
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+dataset_properties={
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+dataset_properties={
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+dataset_properties={
+  'task': 1,
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+  'target_type': 'classification',
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 dataset_properties={
   'task': 1,
   'sparse': False,
@@ -241,7 +345,7 @@
     print("Accuracy score:", sklearn.metrics.accuracy_score(y_test, predictions))
 

 

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Total running time of the script: ( 1 minutes  55.477 seconds)

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Total running time of the script: ( 1 minutes  59.910 seconds)
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Total running time of the script: ( 2 minutes 4.422 seconds)

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Total running time of the script: ( 1 minutes 57.803 seconds)