10227101 1 Jan van Rijn 49 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) 8152533 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": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8]}}] 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 "mean" 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 "friedman_mse" 9667 init null 9667 learning_rate 1.9687418798919585e-05 9667 loss "deviance" 9667 max_depth 24 9667 max_features 0.7805735684922522 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.36004711135664325 9667 min_impurity_split null 9667 min_samples_leaf 10 9667 min_samples_split 4 9667 min_weight_fraction_leaf 0.42569010499862664 9667 n_estimators 1299 9667 n_iter_no_change 1160 9667 presort "auto" 9667 random_state 40960 9667 subsample 0.7620199927305592 9667 tol 0.0001929105199465155 9667 validation_fraction 0.45722992205736634 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 50 tic-tac-toe https://www.openml.org/data/download/50/dataset_50_tic-tac-toe.arff -1 21375118 description https://api.openml.org/data/download/21375118/description.xml -1 21375119 predictions https://api.openml.org/data/download/21375119/predictions.arff area_under_roc_curve 0.6239294237653491 [0.623929,0.623929] average_cost 0 kappa 0 kb_relative_information_score 3.350950321608299 mean_absolute_error 0.45144498075647965 mean_prior_absolute_error 0.45300756784968915 number_of_instances 958 [332,626] predictive_accuracy 0.6534446764091858 prior_entropy 0.9312461581068427 recall 0.6534446764091858 [0,1] relative_absolute_error 0.996550637993474 root_mean_prior_squared_error 0.47587270721768155 root_mean_squared_error 0.4752490336652028 root_relative_squared_error 0.9986894109642783 total_cost 0 area_under_roc_curve 0.6618566618566618 [0.661857,0.661857] area_under_roc_curve 0.6972101972101972 [0.69721,0.69721] area_under_roc_curve 0.7895622895622895 [0.789562,0.789562] area_under_roc_curve 0.6758056758056759 [0.675806,0.675806] area_under_roc_curve 0.7448292448292447 [0.744829,0.744829] area_under_roc_curve 0.8128908128908129 [0.812891,0.812891] area_under_roc_curve 0.683111954459203 [0.683112,0.683112] area_under_roc_curve 0.7084914611005693 [0.708491,0.708491] area_under_roc_curve 0.6898826979472141 [0.689883,0.689883] area_under_roc_curve 0.7766373411534702 [0.776637,0.776637] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kb_relative_information_score 0.4387275497016338 kb_relative_information_score 0.37914692168659636 kb_relative_information_score 0.484712767621463 kb_relative_information_score 0.40189477238071203 kb_relative_information_score 0.44913500315157273 kb_relative_information_score 0.4608995528131171 kb_relative_information_score 0.5343779616173057 kb_relative_information_score 0.5872054704058267 kb_relative_information_score -0.27805229389336183 kb_relative_information_score -0.10709738387656456 mean_absolute_error 0.45021224431397006 mean_absolute_error 0.45047581270833675 mean_absolute_error 0.45000939257794753 mean_absolute_error 0.4503752938790633 mean_absolute_error 0.4501666133392654 mean_absolute_error 0.45011490502036305 mean_absolute_error 0.4529767364734205 mean_absolute_error 0.4527426688545062 mean_absolute_error 0.4539152056714797 mean_absolute_error 0.4535081576620813 mean_prior_absolute_error 0.45214843750000067 mean_prior_absolute_error 0.45214843750000067 mean_prior_absolute_error 0.45214843750000067 mean_prior_absolute_error 0.45214843750000067 mean_prior_absolute_error 0.45214843750000067 mean_prior_absolute_error 0.45214843750000067 mean_prior_absolute_error 0.4553385416666673 mean_prior_absolute_error 0.4553385416666673 mean_prior_absolute_error 0.45325657894736904 mean_prior_absolute_error 0.45325657894736904 number_of_instances 96 [33,63] number_of_instances 96 [33,63] number_of_instances 96 [33,63] number_of_instances 96 [33,63] number_of_instances 96 [33,63] number_of_instances 96 [33,63] number_of_instances 96 [34,62] number_of_instances 96 [34,62] number_of_instances 95 [33,62] number_of_instances 95 [33,62] predictive_accuracy 0.65625 predictive_accuracy 0.65625 predictive_accuracy 0.65625 predictive_accuracy 0.65625 predictive_accuracy 0.65625 predictive_accuracy 0.65625 predictive_accuracy 0.6458333333333333 predictive_accuracy 0.6458333333333333 predictive_accuracy 0.6526315789473683 predictive_accuracy 0.6526315789473683 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 prior_entropy 0.9312461581068427 recall 0.65625 [0,1] recall 0.65625 [0,1] recall 0.65625 [0,1] recall 0.65625 [0,1] recall 0.65625 [0,1] recall 0.65625 [0,1] recall 0.6458333333333334 [0,1] recall 0.6458333333333334 [0,1] recall 0.6526315789473685 [0,1] recall 0.6526315789473685 [0,1] relative_absolute_error 0.9957177930399669 relative_absolute_error 0.9963007175234043 relative_absolute_error 0.9952691533473383 relative_absolute_error 0.9960784037411665 relative_absolute_error 0.9956168726985034 relative_absolute_error 0.9955025113193328 relative_absolute_error 0.9948130786719659 relative_absolute_error 0.9942990268237354 relative_absolute_error 1.0014530990937631 relative_absolute_error 1.0005550470228066 root_mean_prior_squared_error 0.47496916018305874 root_mean_prior_squared_error 0.47496916018305874 root_mean_prior_squared_error 0.47496916018305874 root_mean_prior_squared_error 0.47496916018305874 root_mean_prior_squared_error 0.47496916018305874 root_mean_prior_squared_error 0.47496916018305874 root_mean_prior_squared_error 0.4783155938203006 root_mean_prior_squared_error 0.4783155938203006 root_mean_prior_squared_error 0.4761342715793188 root_mean_prior_squared_error 0.4761342715793188 root_mean_squared_error 0.4743857847592499 root_mean_squared_error 0.47444093840685947 root_mean_squared_error 0.4741205699579967 root_mean_squared_error 0.47448008090980637 root_mean_squared_error 0.4742869590232581 root_mean_squared_error 0.47420663924061107 root_mean_squared_error 0.47786713652942603 root_mean_squared_error 0.4776955025389946 root_mean_squared_error 0.4756662963541025 root_mean_squared_error 0.4753263349516632 root_relative_squared_error 0.9987717614685045 root_relative_squared_error 0.9988878819500708 root_relative_squared_error 0.9982133782649488 root_relative_squared_error 0.9989702925700189 root_relative_squared_error 0.998563693778481 root_relative_squared_error 0.9983945885199078 root_relative_squared_error 0.9990624238543161 root_relative_squared_error 0.9987035938419793 root_relative_squared_error 0.9990171360199213 root_relative_squared_error 0.998303132801225 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 883.8130489966716 usercpu_time_millis 811.157928998 usercpu_time_millis 813.3047359951888 usercpu_time_millis 815.016658991226 usercpu_time_millis 808.5610300040571 usercpu_time_millis 807.438377996732 usercpu_time_millis 809.8308939952403 usercpu_time_millis 807.2975559916813 usercpu_time_millis 832.2525520052295 usercpu_time_millis 808.6776409909362 usercpu_time_millis_testing 2.615589000924956 usercpu_time_millis_testing 2.4823540006764233 usercpu_time_millis_testing 2.6023469981737435 usercpu_time_millis_testing 2.6382679934613407 usercpu_time_millis_testing 2.6034039983642288 usercpu_time_millis_testing 2.572277997387573 usercpu_time_millis_testing 2.517184999305755 usercpu_time_millis_testing 2.813223996781744 usercpu_time_millis_testing 2.6532740012044087 usercpu_time_millis_testing 3.504643995256629 usercpu_time_millis_training 881.1974599957466 usercpu_time_millis_training 808.6755749973236 usercpu_time_millis_training 810.7023889970151 usercpu_time_millis_training 812.3783909977647 usercpu_time_millis_training 805.9576260056929 usercpu_time_millis_training 804.8660999993444 usercpu_time_millis_training 807.3137089959346 usercpu_time_millis_training 804.4843319948995 usercpu_time_millis_training 829.5992780040251 usercpu_time_millis_training 805.1729969956796