10576333 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) 8292615 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 "median" 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 0.3383692962048744 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1347 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 20 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 11 19038 random_state 7609 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.011667872361923948 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 22078932 description https://api.openml.org/data/download/22078932/description.xml -1 22078934 predictions https://api.openml.org/data/download/22078934/predictions.arff area_under_roc_curve 0.9970619444444444 [0.999519,0.998208,0.998619,0.996347,0.997544,0.996297,0.994981,0.999278,0.994267,0.995558] average_cost 0 f_measure 0.9525331623186143 [0.982544,0.948403,0.979798,0.927318,0.962779,0.925373,0.94898,0.977444,0.922693,0.95] kappa 0.9472222222222222 kb_relative_information_score 0.950343221141422 mean_absolute_error 0.012016891559990635 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.9525 [0.985,0.965,0.97,0.925,0.97,0.93,0.93,0.975,0.925,0.95] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9527415423095541 [0.9801,0.932367,0.989796,0.929648,0.955665,0.920792,0.96875,0.979899,0.920398,0.95] predictive_accuracy 0.9525 prior_entropy 3.3219280948872383 relative_absolute_error 0.06676050866661258 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.0864248622772703 root_relative_squared_error 0.28808287425756324 total_cost 0 unweighted_recall 0.9524999999999999 [0.985,0.965,0.97,0.925,0.97,0.93,0.93,0.975,0.925,0.95] area_under_roc_curve 0.9975833333333334 [0.996667,0.998333,1,0.998333,1,0.995,0.999167,1,0.989444,0.998889] area_under_roc_curve 0.9986388888888889 [1,0.998611,1,0.9975,1,0.998056,0.996944,0.998056,0.999167,0.998056] area_under_roc_curve 0.9980833333333333 [1,0.9975,1,0.999444,0.999722,0.996667,0.999444,0.999722,0.990278,0.998056] area_under_roc_curve 0.9990277777777778 [1,0.999167,1,0.997778,0.996944,0.999444,1,1,0.998889,0.998056] area_under_roc_curve 0.9960277777777778 [1,0.996944,0.991944,0.985278,0.997778,0.991667,0.999722,1,0.997778,0.999167] area_under_roc_curve 0.9983055555555557 [1,0.999444,1,1,0.996944,0.997222,0.998611,0.999167,0.998889,0.992778] area_under_roc_curve 0.9973055555555556 [0.998889,0.998056,0.999444,0.998333,0.999722,0.996389,0.997778,0.998889,0.989444,0.996111] area_under_roc_curve 0.9988611111111112 [1,0.999167,1,1,1,1,0.995833,1,0.993611,1] area_under_roc_curve 0.9983055555555557 [0.999444,1,1,0.99,1,0.993889,1,1,0.999722,1] area_under_roc_curve 0.9936388888888886 [0.999722,0.998889,1,0.997222,1,0.999444,0.950278,0.999444,0.995556,0.995833] 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 0.9499494279789529 [0.974359,0.95,1,0.878049,0.97561,0.9,0.974359,1,0.894737,0.952381] f_measure 0.9649968730456535 [1,0.95,1,0.95,1,0.974359,0.95,0.9,0.97561,0.95] f_measure 0.9354375978602029 [0.974359,0.918919,1,0.894737,0.95,0.878049,0.95,0.974359,0.883721,0.930233] f_measure 0.9549107429595233 [1,0.95,0.97561,0.918919,0.904762,0.95,0.952381,1,0.923077,0.974359] f_measure 0.9447825378313184 [0.97561,0.952381,0.918919,0.904762,0.95,0.923077,0.95,1,0.923077,0.95] f_measure 0.9597905315491964 [1,0.952381,0.97561,1,0.974359,0.926829,0.918919,0.97561,0.926829,0.947368] f_measure 0.9450286267872917 [0.974359,0.926829,0.947368,0.926829,0.97561,0.95,0.95,0.97561,0.904762,0.918919] f_measure 0.9647757901929918 [1,0.952381,0.974359,0.952381,0.952381,0.918919,0.974359,1,0.947368,0.97561] f_measure 0.9699624295259724 [0.952381,0.97561,1,0.923077,1,0.926829,0.974359,1,0.947368,1] f_measure 0.9348546176402402 [0.97561,0.952381,1,0.923077,0.947368,0.909091,0.888889,0.947368,0.904762,0.9] kappa 0.9444444444444444 kappa 0.961111111111111 kappa 0.9277777777777778 kappa 0.95 kappa 0.9388888888888889 kappa 0.9555555555555555 kappa 0.9388888888888889 kappa 0.961111111111111 kappa 0.9666666666666667 kappa 0.9277777777777778 kb_relative_information_score 0.9403925917156254 kb_relative_information_score 0.9553520992909412 kb_relative_information_score 0.9407444116951608 kb_relative_information_score 0.9601695478133199 kb_relative_information_score 0.9424709485910308 kb_relative_information_score 0.9570920522668495 kb_relative_information_score 0.9407529800087764 kb_relative_information_score 0.9693690449534407 kb_relative_information_score 0.9618055740156325 kb_relative_information_score 0.935282961063113 mean_absolute_error 0.015186837846226582 mean_absolute_error 0.010281185803246282 mean_absolute_error 0.014661159278018978 mean_absolute_error 0.009676720990241198 mean_absolute_error 0.013610245673062517 mean_absolute_error 0.009031278957319129 mean_absolute_error 0.013682792870783047 mean_absolute_error 0.007668085573287451 mean_absolute_error 0.01145802682341404 mean_absolute_error 0.014912581784307351 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 0.9513059163059164 [1,0.95,1,0.857143,0.952381,0.9,1,1,0.944444,0.909091] precision 0.9652380952380952 [1,0.95,1,0.95,1,1,0.95,0.9,0.952381,0.95] precision 0.9397239475500345 [1,1,1,0.944444,0.95,0.857143,0.95,1,0.826087,0.869565] precision 0.9572476646160857 [1,0.95,0.952381,1,0.863636,0.95,0.909091,1,0.947368,1] precision 0.9469845067213488 [0.952381,0.909091,1,0.863636,0.95,0.947368,0.95,1,0.947368,0.95] precision 0.9623376623376623 [1,0.909091,0.952381,1,1,0.904762,1,0.952381,0.904762,1] precision 0.9477922077922077 [1,0.904762,1,0.904762,0.952381,0.95,0.95,0.952381,0.863636,1] precision 0.9679653679653678 [1,0.909091,1,0.909091,0.909091,1,1,1,1,0.952381] precision 0.9713602187286398 [0.909091,0.952381,1,0.947368,1,0.904762,1,1,1,1] precision 0.940580997949419 [0.952381,0.909091,1,0.947368,1,0.833333,1,1,0.863636,0.9] predictive_accuracy 0.95 predictive_accuracy 0.965 predictive_accuracy 0.935 predictive_accuracy 0.955 predictive_accuracy 0.945 predictive_accuracy 0.96 predictive_accuracy 0.945 predictive_accuracy 0.965 predictive_accuracy 0.97 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 0.08437132136792554 relative_absolute_error 0.05711769890692385 relative_absolute_error 0.0814508848778833 relative_absolute_error 0.053759561056895604 relative_absolute_error 0.07561247596145852 relative_absolute_error 0.05017377198510633 relative_absolute_error 0.07601551594879478 relative_absolute_error 0.04260047540715255 relative_absolute_error 0.06365570457452252 relative_absolute_error 0.08284767657948537 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 0.09121762261304371 root_mean_squared_error 0.0818645711835443 root_mean_squared_error 0.09439866630741013 root_mean_squared_error 0.07681001324112564 root_mean_squared_error 0.09484024887093563 root_mean_squared_error 0.08434439514655234 root_mean_squared_error 0.09605846552969229 root_mean_squared_error 0.07063359953913964 root_mean_squared_error 0.06923404297311131 root_mean_squared_error 0.09869590914913588 root_relative_squared_error 0.3040587420434792 root_relative_squared_error 0.27288190394514783 root_relative_squared_error 0.31466222102470065 root_relative_squared_error 0.256033377470419 root_relative_squared_error 0.31613416290311896 root_relative_squared_error 0.28114798382184136 root_relative_squared_error 0.3201948850989745 root_relative_squared_error 0.23544533179713226 root_relative_squared_error 0.2307801432437045 root_relative_squared_error 0.32898636383045315 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 0.95 [0.95,0.95,1,0.9,1,0.9,0.95,1,0.85,1] unweighted_recall 0.9650000000000001 [1,0.95,1,0.95,1,0.95,0.95,0.9,1,0.95] unweighted_recall 0.9349999999999999 [0.95,0.85,1,0.85,0.95,0.9,0.95,0.95,0.95,1] unweighted_recall 0.9549999999999998 [1,0.95,1,0.85,0.95,0.95,1,1,0.9,0.95] unweighted_recall 0.945 [1,1,0.85,0.95,0.95,0.9,0.95,1,0.9,0.95] unweighted_recall 0.96 [1,1,1,1,0.95,0.95,0.85,1,0.95,0.9] unweighted_recall 0.945 [0.95,0.95,0.9,0.95,1,0.95,0.95,1,0.95,0.85] unweighted_recall 0.9650000000000001 [1,1,0.95,1,1,0.85,0.95,1,0.9,1] unweighted_recall 0.9700000000000001 [1,1,1,0.9,1,0.95,0.95,1,0.9,1] unweighted_recall 0.9349999999999999 [1,1,1,0.9,0.9,1,0.8,0.9,0.95,0.9] usercpu_time_millis 11329.01253899945 usercpu_time_millis 13630.91385899952 usercpu_time_millis 11958.765351000693 usercpu_time_millis 16441.17430499955 usercpu_time_millis 15424.602097000388 usercpu_time_millis 23414.865986999757 usercpu_time_millis 12762.615455000741 usercpu_time_millis 19210.59563400013 usercpu_time_millis 7138.68339200053 usercpu_time_millis 7643.838595000489 usercpu_time_millis_testing 3.485700000055658 usercpu_time_millis_testing 3.9522009992651874 usercpu_time_millis_testing 3.98970000060217 usercpu_time_millis_testing 3.137099000014132 usercpu_time_millis_testing 4.046500000185915 usercpu_time_millis_testing 4.16570099969249 usercpu_time_millis_testing 3.0440000000453438 usercpu_time_millis_testing 3.4471000008124975 usercpu_time_millis_testing 3.714100000252074 usercpu_time_millis_testing 2.933800000391784 usercpu_time_millis_training 11325.526838999394 usercpu_time_millis_training 13626.961658000255 usercpu_time_millis_training 11954.77565100009 usercpu_time_millis_training 16438.037205999535 usercpu_time_millis_training 15420.555597000202 usercpu_time_millis_training 23410.700286000065 usercpu_time_millis_training 12759.571455000696 usercpu_time_millis_training 19207.148533999316 usercpu_time_millis_training 7134.969292000278 usercpu_time_millis_training 7640.904795000097 wall_clock_time_millis 11345.556735992432 wall_clock_time_millis 14045.063734054565 wall_clock_time_millis 11972.501277923584 wall_clock_time_millis 16454.926013946533 wall_clock_time_millis 16166.660070419312 wall_clock_time_millis 23458.754062652588 wall_clock_time_millis 12770.262002944946 wall_clock_time_millis 19229.830026626587 wall_clock_time_millis 7164.406538009644 wall_clock_time_millis 7677.438974380493 wall_clock_time_millis_testing 3.490447998046875 wall_clock_time_millis_testing 3.954648971557617 wall_clock_time_millis_testing 3.9942264556884766 wall_clock_time_millis_testing 3.1397342681884766 wall_clock_time_millis_testing 4.058837890625 wall_clock_time_millis_testing 4.168510437011719 wall_clock_time_millis_testing 3.047466278076172 wall_clock_time_millis_testing 3.449678421020508 wall_clock_time_millis_testing 3.718137741088867 wall_clock_time_millis_testing 2.9363632202148438 wall_clock_time_millis_training 11342.066287994385 wall_clock_time_millis_training 14041.109085083008 wall_clock_time_millis_training 11968.507051467896 wall_clock_time_millis_training 16451.786279678345 wall_clock_time_millis_training 16162.601232528687 wall_clock_time_millis_training 23454.585552215576 wall_clock_time_millis_training 12767.21453666687 wall_clock_time_millis_training 19226.380348205566 wall_clock_time_millis_training 7160.688400268555 wall_clock_time_millis_training 7674.502611160278 weighted_recall 0.95 [0.95,0.95,1,0.9,1,0.9,0.95,1,0.85,1] weighted_recall 0.965 [1,0.95,1,0.95,1,0.95,0.95,0.9,1,0.95] weighted_recall 0.935 [0.95,0.85,1,0.85,0.95,0.9,0.95,0.95,0.95,1] weighted_recall 0.955 [1,0.95,1,0.85,0.95,0.95,1,1,0.9,0.95] weighted_recall 0.945 [1,1,0.85,0.95,0.95,0.9,0.95,1,0.9,0.95] weighted_recall 0.96 [1,1,1,1,0.95,0.95,0.85,1,0.95,0.9] weighted_recall 0.945 [0.95,0.95,0.9,0.95,1,0.95,0.95,1,0.95,0.85] weighted_recall 0.965 [1,1,0.95,1,1,0.85,0.95,1,0.9,1] weighted_recall 0.97 [1,1,1,0.9,1,0.95,0.95,1,0.9,1] weighted_recall 0.935 [1,1,1,0.9,0.9,1,0.8,0.9,0.95,0.9]