10197324 1 Jan van Rijn 9954 Supervised Classification 9666 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4) 8122757 copy true 9559 fill_value -1 9559 missing_values NaN 9559 strategy "constant" 9559 verbose 0 9559 n_jobs null 9606 remainder "passthrough" 9606 sparse_threshold 0.3 9606 transformer_weights null 9606 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}] 9606 memory null 9607 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 9607 axis 0 9608 copy true 9608 missing_values "NaN" 9608 strategy "median" 9608 verbose 0 9608 copy true 9609 with_mean true 9609 with_std true 9609 memory null 9610 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 9610 categorical_features null 9611 categories null 9611 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 9611 handle_unknown "ignore" 9611 n_values null 9611 sparse true 9611 threshold 0.0 9612 memory null 9666 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 9666 criterion "mae" 9667 init null 9667 learning_rate 0.00010916227621173997 9667 loss "deviance" 9667 max_depth 5 9667 max_features 0.2749770967205287 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.5815772633472427 9667 min_impurity_split null 9667 min_samples_leaf 2 9667 min_samples_split 9 9667 min_weight_fraction_leaf 0.20303622259109472 9667 n_estimators 204 9667 n_iter_no_change 899 9667 presort "auto" 9667 random_state 14446 9667 subsample 0.505139743002011 9667 tol 0.0007259523441537901 9667 validation_fraction 0.4369952137230827 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 21315564 description https://api.openml.org/data/download/21315564/description.xml -1 21315566 predictions https://api.openml.org/data/download/21315566/predictions.arff area_under_roc_curve 0.5002525252525252 [0.5,0.525253,0.550505,0.474747,0.474747,0.550505,0.474747,0.575758,0.474747,0.525253,0.424242,0.525253,0.449495,0.575758,0.525253,0.525253,0.474747,0.550505,0.424242,0.575758,0.550505,0.449495,0.575758,0.550505,0.424242,0.575758,0.474747,0.525253,0.474747,0.575758,0.424242,0.474747,0.575758,0.550505,0.424242,0.550505,0.525253,0.474747,0.449495,0.525253,0.550505,0.449495,0.474747,0.449495,0.474747,0.424242,0.525253,0.575758,0.575758,0.550505,0.474747,0.449495,0.474747,0.5,0.525253,0.525253,0.474747,0.550505,0.424242,0.525253,0.474747,0.5,0.525253,0.424242,0.550505,0.575758,0.474747,0.550505,0.474747,0.525253,0.525253,0.575758,0.474747,0.525253,0.474747,0.474747,0.424242,0.550505,0.5,0.474747,0.424242,0.550505,0.424242,0.424242,0.424242,0.424242,0.424242,0.474747,0.424242,0.474747,0.525253,0.474747,0.449495,0.5,0.525253,0.525253,0.550505,0.575758,0.474747,0.575758] average_cost 0 kappa 0.002525252525252526 kb_relative_information_score 1.0356915507820827 mean_absolute_error 0.019799999087772194 mean_prior_absolute_error 0.019800000000000036 number_of_instances 1600 [16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] predictive_accuracy 0.0125 prior_entropy 6.6438561897747395 recall 0.0125 [0,0,0,0,0.25,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 0.9999999539278868 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09949876716664702 root_relative_squared_error 1.0000002357415185 total_cost 0 area_under_roc_curve 0.5 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0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kb_relative_information_score 0.10364865053390565 kb_relative_information_score 0.10364865053390565 kb_relative_information_score 0.10326608276474072 kb_relative_information_score 0.10326608276474072 kb_relative_information_score 0.10025946342484718 kb_relative_information_score 0.10025946342484718 kb_relative_information_score 0.10480308984461317 kb_relative_information_score 0.10480308984461317 kb_relative_information_score 0.10586848882293333 kb_relative_information_score 0.10586848882293333 mean_absolute_error 0.019800005994276736 mean_absolute_error 0.019800005994276736 mean_absolute_error 0.01979999843861941 mean_absolute_error 0.01979999843861941 mean_absolute_error 0.01980003659402096 mean_absolute_error 0.01980003659402096 mean_absolute_error 0.01979997207761385 mean_absolute_error 0.01979997207761385 mean_absolute_error 0.01979998233432994 mean_absolute_error 0.01979998233432994 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.0125 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 recall 0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 1.0000003027412476 relative_absolute_error 1.0000003027412476 relative_absolute_error 0.9999999211423928 relative_absolute_error 0.9999999211423928 relative_absolute_error 1.0000018481828752 relative_absolute_error 1.0000018481828752 relative_absolute_error 0.9999985897784756 relative_absolute_error 0.9999985897784756 relative_absolute_error 0.9999991077944398 relative_absolute_error 0.9999991077944398 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_squared_error 0.09949880216052659 root_mean_squared_error 0.09949880216052659 root_mean_squared_error 0.09949876312379619 root_mean_squared_error 0.09949876312379619 root_mean_squared_error 0.09949895493574679 root_mean_squared_error 0.09949895493574679 root_mean_squared_error 0.09949863159925677 root_mean_squared_error 0.09949863159925677 root_mean_squared_error 0.0994986840135984 root_mean_squared_error 0.0994986840135984 root_relative_squared_error 1.0000005874432416 root_relative_squared_error 1.0000005874432416 root_relative_squared_error 1.0000001951093391 root_relative_squared_error 1.0000001951093391 root_relative_squared_error 1.0000021228919769 root_relative_squared_error 1.0000021228919769 root_relative_squared_error 0.9999988732379816 root_relative_squared_error 0.9999988732379816 root_relative_squared_error 0.9999994000219357 root_relative_squared_error 0.9999994000219357 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 usercpu_time_millis 75448.96661799998 usercpu_time_millis 74996.539621 usercpu_time_millis 75238.75923799996 usercpu_time_millis 75108.17619900001 usercpu_time_millis 74736.8786369999 usercpu_time_millis 74943.39925099995 usercpu_time_millis 74970.67059200002 usercpu_time_millis 75264.56682499997 usercpu_time_millis 74807.419096 usercpu_time_millis 75097.99470000007 usercpu_time_millis_testing 14.397808000012446 usercpu_time_millis_testing 11.844440000004397 usercpu_time_millis_testing 15.708488999962356 usercpu_time_millis_testing 13.789406999990206 usercpu_time_millis_testing 14.08814399997027 usercpu_time_millis_testing 12.044513999967421 usercpu_time_millis_testing 15.777316000026076 usercpu_time_millis_testing 10.94941500002733 usercpu_time_millis_testing 13.322087000005922 usercpu_time_millis_testing 11.878892000140695 usercpu_time_millis_training 75434.56880999997 usercpu_time_millis_training 74984.695181 usercpu_time_millis_training 75223.05074899999 usercpu_time_millis_training 75094.38679200002 usercpu_time_millis_training 74722.79049299993 usercpu_time_millis_training 74931.35473699999 usercpu_time_millis_training 74954.893276 usercpu_time_millis_training 75253.61740999995 usercpu_time_millis_training 74794.09700899999 usercpu_time_millis_training 75086.11580799993