10576288 28997 Marc Boel 16 Supervised Classification 19037 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(1) 8292570 Python_3.8.10. Sklearn_0.24.2. NumPy_1.17.4. SciPy_1.3.3. add_indicator false 18819 copy true 18819 fill_value null 18819 missing_values NaN 18819 strategy "mean" 18819 verbose 0 18819 n_jobs null 18996 remainder "drop" 18996 sparse_threshold 0.3 18996 transformer_weights null 18996 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}] 18996 verbose false 18996 categories "auto" 18997 drop null 18997 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 18997 handle_unknown "ignore" 18997 sparse true 18997 memory null 19037 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 19037 verbose false 19037 ccp_alpha 0.0 19038 criterion "friedman_mse" 19038 init null 19038 learning_rate 0.3769214775400738 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 540 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 177 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 10 19038 random_state 21971 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.2962205297286032 19038 verbose 0 19038 warm_start false 19038 openml-python Sklearn_0.24.2. 16 mfeat-karhunen https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff -1 22078843 description https://api.openml.org/data/download/22078843/description.xml -1 22078844 predictions https://api.openml.org/data/download/22078844/predictions.arff area_under_roc_curve 0.9971891666666667 [0.998878,0.997672,0.999847,0.995075,0.998108,0.994781,0.993575,0.999392,0.997353,0.997211] average_cost 0 f_measure 0.9500075303963534 [0.974874,0.926108,0.985,0.936709,0.950495,0.925373,0.956743,0.968059,0.93199,0.944724] kappa 0.9444444444444444 kb_relative_information_score 0.9444802515732746 mean_absolute_error 0.013791731034891215 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.95 [0.97,0.94,0.985,0.925,0.96,0.93,0.94,0.985,0.925,0.94] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9502471166951322 [0.979798,0.912621,0.985,0.948718,0.941176,0.920792,0.974093,0.951691,0.939086,0.949495] predictive_accuracy 0.95 prior_entropy 3.3219280948872383 relative_absolute_error 0.07662072797161551 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.08771958173473939 root_relative_squared_error 0.2923986057824602 total_cost 0 unweighted_recall 0.95 [0.97,0.94,0.985,0.925,0.96,0.93,0.94,0.985,0.925,0.94] area_under_roc_curve 0.9977777777777779 [0.997778,0.997222,1,0.998611,1,0.992222,0.9975,1,0.994444,1] area_under_roc_curve 0.9985555555555556 [1,0.9975,1,0.995556,0.998333,0.995556,0.999722,0.999167,1,0.999722] area_under_roc_curve 0.9980833333333333 [0.999722,0.998056,1,0.998333,1,0.990833,1,0.998056,0.998611,0.997222] area_under_roc_curve 0.9974166666666667 [1,1,0.999722,0.989444,0.995833,0.994444,1,0.999444,0.999722,0.995556] area_under_roc_curve 0.997361111111111 [0.999722,0.993611,1,0.990556,0.997778,0.993333,0.999722,1,0.999167,0.999722] area_under_roc_curve 0.9967777777777778 [1,0.998056,1,1,0.996667,0.988333,0.996944,1,0.996389,0.991389] area_under_roc_curve 0.9973888888888888 [0.993611,0.995278,0.999722,0.999444,1,0.997778,1,0.998333,0.995556,0.994167] area_under_roc_curve 0.9985833333333334 [1,0.999722,1,0.998611,0.998056,0.999722,0.994444,1,0.995278,1] area_under_roc_curve 0.9980000000000001 [0.996944,1,1,0.989167,1,0.993889,1,1,1,1] area_under_roc_curve 0.9955833333333333 [1,0.998611,1,0.997778,0.999444,0.998611,0.966389,1,0.997222,0.997778] 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 f_measure 0.94489729470474 [0.974359,0.923077,1,0.918919,0.952381,0.926829,0.947368,0.97561,0.878049,0.952381] f_measure 0.955191590608792 [1,0.904762,1,0.9,0.947368,0.923077,0.974359,0.952381,0.97561,0.974359] f_measure 0.9505016334454791 [0.974359,0.974359,1,0.918919,0.97561,0.878049,1,0.95,0.95,0.883721] f_measure 0.9653027585106575 [0.974359,0.930233,0.952381,0.947368,0.95,0.974359,1,0.97561,0.974359,0.974359] f_measure 0.9397936585035428 [0.97561,0.878049,0.947368,0.9,0.918919,0.9,0.952381,1,0.97561,0.95] f_measure 0.9440984712935933 [0.97561,0.952381,1,1,0.95,0.926829,0.918919,0.952381,0.9,0.864865] f_measure 0.9549104550503184 [0.974359,0.894737,0.974359,0.97561,0.97561,0.926829,1,0.930233,0.95,0.947368] f_measure 0.958978317012917 [0.97561,0.930233,1,0.926829,0.97561,0.974359,0.95,1,0.857143,1] f_measure 0.9503635196639046 [0.95,0.947368,0.97561,0.926829,0.909091,0.9,0.947368,1,0.947368,1] f_measure 0.9351942708553749 [0.974359,0.926829,1,0.95,0.95,0.926829,0.871795,0.947368,0.904762,0.9] kappa 0.9388888888888889 kappa 0.95 kappa 0.9444444444444444 kappa 0.961111111111111 kappa 0.9333333333333332 kappa 0.9388888888888889 kappa 0.95 kappa 0.9555555555555555 kappa 0.9444444444444444 kappa 0.9277777777777778 kb_relative_information_score 0.9390419286950329 kb_relative_information_score 0.9468296951355106 kb_relative_information_score 0.9442230866916251 kb_relative_information_score 0.9583420847989873 kb_relative_information_score 0.9257184619026709 kb_relative_information_score 0.9321642879637254 kb_relative_information_score 0.9462896587980826 kb_relative_information_score 0.9587907751822771 kb_relative_information_score 0.957009684961478 kb_relative_information_score 0.9363928516030379 mean_absolute_error 0.015551824809918593 mean_absolute_error 0.012602200977852713 mean_absolute_error 0.013866668371352801 mean_absolute_error 0.010538697095594945 mean_absolute_error 0.01875742438890405 mean_absolute_error 0.017063814524412097 mean_absolute_error 0.013448118643353397 mean_absolute_error 0.010165468467206219 mean_absolute_error 0.011607561289751498 mean_absolute_error 0.014315531780566033 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.9479835953520164 [1,0.947368,1,1,0.909091,0.904762,1,0.952381,0.857143,0.909091] precision 0.9572476646160857 [1,0.863636,1,0.9,1,0.947368,1,0.909091,0.952381,1] precision 0.9535610766045549 [1,1,1,1,0.952381,0.857143,1,0.95,0.95,0.826087] precision 0.9681037078863164 [1,0.869565,0.909091,1,0.95,1,1,0.952381,1,1] precision 0.942099567099567 [0.952381,0.857143,1,0.9,1,0.9,0.909091,1,0.952381,0.95] precision 0.946650114591291 [0.952381,0.909091,1,1,0.95,0.904762,1,0.909091,0.9,0.941176] precision 0.9573533471359559 [1,0.944444,1,0.952381,0.952381,0.904762,1,0.869565,0.95,1] precision 0.9629089026915113 [0.952381,0.869565,1,0.904762,0.952381,1,0.95,1,1,1] precision 0.954047619047619 [0.95,1,0.952381,0.904762,0.833333,0.9,1,1,1,1] precision 0.9367897015265437 [1,0.904762,1,0.95,0.95,0.904762,0.894737,1,0.863636,0.9] predictive_accuracy 0.945 predictive_accuracy 0.955 predictive_accuracy 0.95 predictive_accuracy 0.965 predictive_accuracy 0.94 predictive_accuracy 0.945 predictive_accuracy 0.955 predictive_accuracy 0.96 predictive_accuracy 0.95 predictive_accuracy 0.935 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 relative_absolute_error 0.08639902672177005 relative_absolute_error 0.07001222765473737 relative_absolute_error 0.07703704650751565 relative_absolute_error 0.05854831719774976 relative_absolute_error 0.10420791327168928 relative_absolute_error 0.09479896958006732 relative_absolute_error 0.0747117702408523 relative_absolute_error 0.05647482481781238 relative_absolute_error 0.06448645160973061 relative_absolute_error 0.07953073211425582 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.08775392611181179 root_mean_squared_error 0.0871637276587532 root_mean_squared_error 0.09085045989589895 root_mean_squared_error 0.07292418996867156 root_mean_squared_error 0.09786356564117855 root_mean_squared_error 0.09785930121034923 root_mean_squared_error 0.0841743717642475 root_mean_squared_error 0.07533500689647075 root_mean_squared_error 0.07905558822044736 root_mean_squared_error 0.0995642768046111 root_relative_squared_error 0.2925130870393728 root_relative_squared_error 0.2905457588625109 root_relative_squared_error 0.3028348663196634 root_relative_squared_error 0.24308063322890533 root_relative_squared_error 0.3262118854705954 root_relative_squared_error 0.3261976707011643 root_relative_squared_error 0.2805812392141585 root_relative_squared_error 0.2511166896549027 root_relative_squared_error 0.26351862740149135 root_relative_squared_error 0.33188092268203717 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 unweighted_recall 0.9450000000000001 [0.95,0.9,1,0.85,1,0.95,0.9,1,0.9,1] unweighted_recall 0.9550000000000001 [1,0.95,1,0.9,0.9,0.9,0.95,1,1,0.95] unweighted_recall 0.95 [0.95,0.95,1,0.85,1,0.9,1,0.95,0.95,0.95] unweighted_recall 0.9649999999999999 [0.95,1,1,0.9,0.95,0.95,1,1,0.95,0.95] unweighted_recall 0.9399999999999998 [1,0.9,0.9,0.9,0.85,0.9,1,1,1,0.95] unweighted_recall 0.9450000000000001 [1,1,1,1,0.95,0.95,0.85,1,0.9,0.8] unweighted_recall 0.9550000000000001 [0.95,0.85,0.95,1,1,0.95,1,1,0.95,0.9] unweighted_recall 0.9600000000000002 [1,1,1,0.95,1,0.95,0.95,1,0.75,1] unweighted_recall 0.95 [0.95,0.9,1,0.95,1,0.9,0.9,1,0.9,1] unweighted_recall 0.9349999999999999 [0.95,0.95,1,0.95,0.95,0.95,0.85,0.9,0.95,0.9] usercpu_time_millis 5796.784373999799 usercpu_time_millis 6567.250574999889 usercpu_time_millis 6446.10787900001 usercpu_time_millis 6980.074088000038 usercpu_time_millis 5800.259470999663 usercpu_time_millis 5885.632372000146 usercpu_time_millis 6347.7320820002205 usercpu_time_millis 7412.468594000529 usercpu_time_millis 6191.232377999768 usercpu_time_millis 7171.001391000573 usercpu_time_millis_testing 4.64410000040516 usercpu_time_millis_testing 3.0841999996482627 usercpu_time_millis_testing 4.158699999607052 usercpu_time_millis_testing 3.1260000005204347 usercpu_time_millis_testing 3.762000000278931 usercpu_time_millis_testing 3.7573999998130603 usercpu_time_millis_testing 4.638800000066112 usercpu_time_millis_testing 3.2973000006677466 usercpu_time_millis_testing 3.9608999995834893 usercpu_time_millis_testing 3.18589900052757 usercpu_time_millis_training 5792.140273999394 usercpu_time_millis_training 6564.166375000241 usercpu_time_millis_training 6441.949179000403 usercpu_time_millis_training 6976.948087999517 usercpu_time_millis_training 5796.497470999384 usercpu_time_millis_training 5881.8749720003325 usercpu_time_millis_training 6343.093282000154 usercpu_time_millis_training 7409.1712939998615 usercpu_time_millis_training 6187.271478000184 usercpu_time_millis_training 7167.815492000045 wall_clock_time_millis 5930.474042892456 wall_clock_time_millis 6949.768543243408 wall_clock_time_millis 6451.91764831543 wall_clock_time_millis 6993.796586990356 wall_clock_time_millis 5805.266380310059 wall_clock_time_millis 6166.12696647644 wall_clock_time_millis 6354.764223098755 wall_clock_time_millis 7540.453672409058 wall_clock_time_millis 6379.693984985352 wall_clock_time_millis 7194.236755371094 wall_clock_time_millis_testing 4.647254943847656 wall_clock_time_millis_testing 3.0875205993652344 wall_clock_time_millis_testing 4.162073135375977 wall_clock_time_millis_testing 3.129720687866211 wall_clock_time_millis_testing 3.7643909454345703 wall_clock_time_millis_testing 3.7610530853271484 wall_clock_time_millis_testing 4.644155502319336 wall_clock_time_millis_testing 3.2987594604492188 wall_clock_time_millis_testing 3.965616226196289 wall_clock_time_millis_testing 3.2024383544921875 wall_clock_time_millis_training 5925.826787948608 wall_clock_time_millis_training 6946.681022644043 wall_clock_time_millis_training 6447.755575180054 wall_clock_time_millis_training 6990.66686630249 wall_clock_time_millis_training 5801.501989364624 wall_clock_time_millis_training 6162.365913391113 wall_clock_time_millis_training 6350.120067596436 wall_clock_time_millis_training 7537.154912948608 wall_clock_time_millis_training 6375.728368759155 wall_clock_time_millis_training 7191.034317016602 weighted_recall 0.945 [0.95,0.9,1,0.85,1,0.95,0.9,1,0.9,1] weighted_recall 0.955 [1,0.95,1,0.9,0.9,0.9,0.95,1,1,0.95] weighted_recall 0.95 [0.95,0.95,1,0.85,1,0.9,1,0.95,0.95,0.95] weighted_recall 0.965 [0.95,1,1,0.9,0.95,0.95,1,1,0.95,0.95] weighted_recall 0.94 [1,0.9,0.9,0.9,0.85,0.9,1,1,1,0.95] weighted_recall 0.945 [1,1,1,1,0.95,0.95,0.85,1,0.9,0.8] weighted_recall 0.955 [0.95,0.85,0.95,1,1,0.95,1,1,0.95,0.9] weighted_recall 0.96 [1,1,1,0.95,1,0.95,0.95,1,0.75,1] weighted_recall 0.95 [0.95,0.9,1,0.95,1,0.9,0.9,1,0.9,1] weighted_recall 0.935 [0.95,0.95,1,0.95,0.95,0.95,0.85,0.9,0.95,0.9]