10576496 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) 8292778 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 0.41893294012637605 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1802 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 119 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 1 19038 random_state 52187 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.28023655397500624 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 22079259 description https://api.openml.org/data/download/22079259/description.xml -1 22079260 predictions https://api.openml.org/data/download/22079260/predictions.arff area_under_roc_curve 0.996166388888889 [0.999033,0.994569,0.999508,0.996444,0.99715,0.992514,0.993283,0.998922,0.994775,0.995464] average_cost 0 f_measure 0.9401114372205925 [0.967419,0.921569,0.969849,0.929293,0.947368,0.910891,0.943878,0.952854,0.910891,0.947103] kappa 0.9333333333333332 kb_relative_information_score 0.9240038085940669 mean_absolute_error 0.02059478068839761 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.94 [0.965,0.94,0.965,0.92,0.945,0.92,0.925,0.96,0.92,0.94] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9404557892735533 [0.969849,0.903846,0.974747,0.938776,0.949749,0.901961,0.963542,0.945813,0.901961,0.954315] predictive_accuracy 0.94 prior_entropy 3.3219280948872383 relative_absolute_error 0.11441544826887208 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.09725729947482814 root_relative_squared_error 0.32419099824942216 total_cost 0 unweighted_recall 0.9399999999999998 [0.965,0.94,0.965,0.92,0.945,0.92,0.925,0.96,0.92,0.94] area_under_roc_curve 0.9975 [0.996667,0.998056,1,1,0.999444,0.990278,0.997222,1,0.994167,0.999167] area_under_roc_curve 0.9979444444444444 [1,0.991944,1,0.998333,1,0.993611,0.999722,0.997778,0.999167,0.998889] area_under_roc_curve 0.9960555555555556 [0.999722,0.982222,0.999722,0.999444,1,0.988333,1,0.9975,0.996389,0.997222] area_under_roc_curve 0.9980277777777776 [1,0.999167,1,0.996944,0.997222,0.991111,1,0.997778,0.999167,0.998889] area_under_roc_curve 0.9962777777777778 [1,0.995,0.998056,0.990556,0.994167,0.986389,0.999722,1,0.998889,1] area_under_roc_curve 0.9941388888888889 [1,0.994167,0.999722,0.998611,0.987778,0.989444,0.994444,0.999167,0.995278,0.982778] area_under_roc_curve 0.9970277777777778 [0.998056,0.993333,0.999444,1,1,0.996111,1,0.999167,0.995278,0.988889] area_under_roc_curve 0.9971388888888888 [1,0.997778,1,0.9975,0.999167,0.9975,0.997778,0.999167,0.983056,0.999444] area_under_roc_curve 0.9970833333333333 [0.999167,1,0.999722,0.988056,0.997778,0.991111,0.996111,1,0.998889,1] area_under_roc_curve 0.9951111111111111 [1,0.998056,1,0.998056,1,0.998333,0.9725,1,0.9925,0.991667] 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 0.944933299477587 [0.947368,0.9,1,0.974359,0.952381,0.926829,0.894737,1,0.878049,0.97561] f_measure 0.9400459015464837 [0.97561,0.926829,0.974359,0.947368,0.974359,0.871795,0.930233,0.926829,0.95,0.923077] f_measure 0.9353884946888797 [0.974359,0.894737,0.95,0.947368,0.97561,0.857143,1,0.923077,0.904762,0.926829] f_measure 0.9600875076998311 [0.974359,0.952381,0.97561,0.947368,0.974359,0.95,0.97561,0.95,0.926829,0.974359] f_measure 0.939790352993177 [0.97561,0.904762,0.923077,0.894737,0.947368,0.9,0.974359,0.97561,0.95,0.952381] f_measure 0.9147747767943606 [0.952381,0.888889,0.974359,0.947368,0.864865,0.883721,0.864865,0.952381,0.9,0.918919] f_measure 0.9301667244721847 [0.947368,0.864865,0.974359,0.930233,0.952381,0.923077,1,0.926829,0.863636,0.918919] f_measure 0.9495749849921864 [1,0.95,0.97561,0.904762,0.952381,0.947368,0.974359,0.95,0.888889,0.952381] f_measure 0.9498187211601845 [0.95,1,0.95,0.9,0.926829,0.926829,0.918919,0.97561,0.95,1] f_measure 0.9349984094579132 [0.97561,0.930233,1,0.904762,0.947368,0.926829,0.894737,0.947368,0.9,0.923077] kappa 0.9388888888888889 kappa 0.9333333333333332 kappa 0.9277777777777778 kappa 0.9555555555555555 kappa 0.9333333333333332 kappa 0.9055555555555556 kappa 0.9222222222222223 kappa 0.9444444444444444 kappa 0.9444444444444444 kappa 0.9277777777777778 kb_relative_information_score 0.9178155489602081 kb_relative_information_score 0.9171765723442055 kb_relative_information_score 0.9246440930744854 kb_relative_information_score 0.9476374975149865 kb_relative_information_score 0.9222767096438419 kb_relative_information_score 0.899034911520053 kb_relative_information_score 0.9211034816910467 kb_relative_information_score 0.9283452425299825 kb_relative_information_score 0.9267331421683122 kb_relative_information_score 0.9352708864932328 mean_absolute_error 0.023550385198396976 mean_absolute_error 0.023868294657461212 mean_absolute_error 0.02010234249212606 mean_absolute_error 0.013604534060230149 mean_absolute_error 0.021508107255337913 mean_absolute_error 0.026917841844673173 mean_absolute_error 0.020176031754500338 mean_absolute_error 0.01891734138733655 mean_absolute_error 0.021198592324875754 mean_absolute_error 0.016104335909037912 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 0.9467821067821067 [1,0.9,1,1,0.909091,0.904762,0.944444,1,0.857143,0.952381] precision 0.9423575242453961 [0.952381,0.904762,1,1,1,0.894737,0.869565,0.904762,0.95,0.947368] precision 0.9380773904458115 [1,0.944444,0.95,1,0.952381,0.818182,1,0.947368,0.863636,0.904762] precision 0.9618614718614719 [1,0.909091,0.952381,1,1,0.95,0.952381,0.95,0.904762,1] precision 0.9419302042986253 [0.952381,0.863636,0.947368,0.944444,1,0.9,1,0.952381,0.95,0.909091] precision 0.9226621715880029 [0.909091,0.8,1,1,0.941176,0.826087,0.941176,0.909091,0.9,1] precision 0.9363629589551653 [1,0.941176,1,0.869565,0.909091,0.947368,1,0.904762,0.791667,1] precision 0.9534199134199135 [1,0.95,0.952381,0.863636,0.909091,1,1,0.95,1,0.909091] precision 0.9511904761904763 [0.95,1,0.95,0.9,0.904762,0.904762,1,0.952381,0.95,1] precision 0.9382157303667601 [0.952381,0.869565,1,0.863636,1,0.904762,0.944444,1,0.9,0.947368] predictive_accuracy 0.945 predictive_accuracy 0.94 predictive_accuracy 0.935 predictive_accuracy 0.96 predictive_accuracy 0.94 predictive_accuracy 0.915 predictive_accuracy 0.93 predictive_accuracy 0.95 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 0.1308354733244278 relative_absolute_error 0.13260163698589578 relative_absolute_error 0.11167968051181157 relative_absolute_error 0.07558074477905646 relative_absolute_error 0.11948948475187741 relative_absolute_error 0.14954356580374 relative_absolute_error 0.11208906530277979 relative_absolute_error 0.10509634104075871 relative_absolute_error 0.11776995736042098 relative_absolute_error 0.0894685328279885 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 0.09564864547152277 root_mean_squared_error 0.09597376053041996 root_mean_squared_error 0.09898639169425012 root_mean_squared_error 0.07890914150142048 root_mean_squared_error 0.09951257043630712 root_mean_squared_error 0.11737708226790733 root_mean_squared_error 0.09962637888551246 root_mean_squared_error 0.09188928244897535 root_mean_squared_error 0.09116481932972578 root_mean_squared_error 0.09922211229620732 root_relative_squared_error 0.3188288182384094 root_relative_squared_error 0.31991253510140005 root_relative_squared_error 0.32995463898083394 root_relative_squared_error 0.26303047167140176 root_relative_squared_error 0.33170856812102395 root_relative_squared_error 0.3912569408930247 root_relative_squared_error 0.332087929618375 root_relative_squared_error 0.3062976081632513 root_relative_squared_error 0.3038827310990861 root_relative_squared_error 0.33074037432069125 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 0.945 [0.9,0.9,1,0.95,1,0.95,0.85,1,0.9,1] unweighted_recall 0.9400000000000001 [1,0.95,0.95,0.9,0.95,0.85,1,0.95,0.95,0.9] unweighted_recall 0.9349999999999999 [0.95,0.85,0.95,0.9,1,0.9,1,0.9,0.95,0.95] unweighted_recall 0.96 [0.95,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95] unweighted_recall 0.9400000000000001 [1,0.95,0.9,0.85,0.9,0.9,0.95,1,0.95,1] unweighted_recall 0.915 [1,1,0.95,0.9,0.8,0.95,0.8,1,0.9,0.85] unweighted_recall 0.93 [0.9,0.8,0.95,1,1,0.9,1,0.95,0.95,0.85] unweighted_recall 0.9500000000000002 [1,0.95,1,0.95,1,0.9,0.95,0.95,0.8,1] unweighted_recall 0.95 [0.95,1,0.95,0.9,0.95,0.95,0.85,1,0.95,1] unweighted_recall 0.9350000000000002 [1,1,1,0.95,0.9,0.95,0.85,0.9,0.9,0.9] usercpu_time_millis 2869.9559360011335 usercpu_time_millis 2575.062234000143 usercpu_time_millis 3568.7932429991633 usercpu_time_millis 3689.1380460010623 usercpu_time_millis 3717.894944001273 usercpu_time_millis 2875.7472340003005 usercpu_time_millis 3735.1856430004773 usercpu_time_millis 2866.7535349995887 usercpu_time_millis 2564.125230999707 usercpu_time_millis 4774.747564999416 usercpu_time_millis_testing 3.051499999855878 usercpu_time_millis_testing 2.8187000007164897 usercpu_time_millis_testing 3.1767999989824602 usercpu_time_millis_testing 3.380900000593101 usercpu_time_millis_testing 2.7370000007067574 usercpu_time_millis_testing 2.8720000000248547 usercpu_time_millis_testing 2.5415999998585903 usercpu_time_millis_testing 3.29169999986334 usercpu_time_millis_testing 3.279399999883026 usercpu_time_millis_testing 2.7496000002429355 usercpu_time_millis_training 2866.9044360012776 usercpu_time_millis_training 2572.2435339994263 usercpu_time_millis_training 3565.616443000181 usercpu_time_millis_training 3685.757146000469 usercpu_time_millis_training 3715.157944000566 usercpu_time_millis_training 2872.8752340002757 usercpu_time_millis_training 3732.6440430006187 usercpu_time_millis_training 2863.4618349997254 usercpu_time_millis_training 2560.845830999824 usercpu_time_millis_training 4771.997964999173 wall_clock_time_millis 2873.2264041900635 wall_clock_time_millis 2579.3185234069824 wall_clock_time_millis 3572.617530822754 wall_clock_time_millis 3690.9680366516113 wall_clock_time_millis 3728.121757507324 wall_clock_time_millis 2878.7546157836914 wall_clock_time_millis 3747.35426902771 wall_clock_time_millis 2869.1580295562744 wall_clock_time_millis 2565.38987159729 wall_clock_time_millis 4782.706499099731 wall_clock_time_millis_testing 3.0558109283447266 wall_clock_time_millis_testing 2.8228759765625 wall_clock_time_millis_testing 3.1812191009521484 wall_clock_time_millis_testing 3.3845901489257812 wall_clock_time_millis_testing 2.7403831481933594 wall_clock_time_millis_testing 2.8765201568603516 wall_clock_time_millis_testing 2.5446414947509766 wall_clock_time_millis_testing 3.2956600189208984 wall_clock_time_millis_testing 3.2851696014404297 wall_clock_time_millis_testing 2.756357192993164 wall_clock_time_millis_training 2870.1705932617188 wall_clock_time_millis_training 2576.49564743042 wall_clock_time_millis_training 3569.4363117218018 wall_clock_time_millis_training 3687.5834465026855 wall_clock_time_millis_training 3725.381374359131 wall_clock_time_millis_training 2875.878095626831 wall_clock_time_millis_training 3744.809627532959 wall_clock_time_millis_training 2865.8623695373535 wall_clock_time_millis_training 2562.1047019958496 wall_clock_time_millis_training 4779.950141906738 weighted_recall 0.945 [0.9,0.9,1,0.95,1,0.95,0.85,1,0.9,1] weighted_recall 0.94 [1,0.95,0.95,0.9,0.95,0.85,1,0.95,0.95,0.9] weighted_recall 0.935 [0.95,0.85,0.95,0.9,1,0.9,1,0.9,0.95,0.95] weighted_recall 0.96 [0.95,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95] weighted_recall 0.94 [1,0.95,0.9,0.85,0.9,0.9,0.95,1,0.95,1] weighted_recall 0.915 [1,1,0.95,0.9,0.8,0.95,0.8,1,0.9,0.85] weighted_recall 0.93 [0.9,0.8,0.95,1,1,0.9,1,0.95,0.95,0.85] weighted_recall 0.95 [1,0.95,1,0.95,1,0.9,0.95,0.95,0.8,1] weighted_recall 0.95 [0.95,1,0.95,0.9,0.95,0.95,0.85,1,0.95,1] weighted_recall 0.935 [1,1,1,0.95,0.9,0.95,0.85,0.9,0.9,0.9]