10588196 32117 VAIBHAV JAISWAL 18 Supervised Classification 19162 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.tree._classes.DecisionTreeClassifier)(1) 8304103 Python_3.7.7. Sklearn_1.0.2. NumPy_1.21.6. SciPy_1.7.3. copy true 19075 with_mean true 19075 with_std true 19075 add_indicator false 19084 copy true 19084 fill_value null 19084 missing_values NaN 19084 strategy "mean" 19084 verbose 0 19084 ccp_alpha 0.0 19085 class_weight null 19085 criterion "gini" 19085 max_depth null 19085 max_features null 19085 max_leaf_nodes null 19085 min_impurity_decrease 0.0 19085 min_samples_leaf 1 19085 min_samples_split 2 19085 min_weight_fraction_leaf 0.0 19085 random_state 0 19085 splitter "best" 19085 memory null 19156 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "scaler", "step_name": "scaler"}}] 19156 verbose false 19156 memory null 19162 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "numerical", "step_name": "numerical"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "model", "step_name": "model"}}] 19162 verbose false 19162 openml-python Sklearn_1.0.2. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22103959 description https://api.openml.org/data/download/22103959/description.xml -1 22103960 predictions https://api.openml.org/data/download/22103960/predictions.arff area_under_roc_curve 0.5156752777777779 [0.991389,0.4575,0.494722,0.545833,0.460833,0.434722,0.443889,0.444722,0.437586,0.445556] average_cost 0 f_measure 0.130967882346316 [0.982544,0.029056,0.090226,0.182278,0.025575,0,0,0,0,0] kappa 0.034444444444444444 kb_relative_information_score 0.09198146819767429 mean_absolute_error 0.17369999999999444 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.131 [0.985,0.03,0.09,0.18,0.025,0,0,0,0,0] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.13095141729651905 [0.9801,0.028169,0.090452,0.184615,0.026178,0,0,0,0,0] predictive_accuracy 0.131 prior_entropy 3.3219280948872383 relative_absolute_error 0.9649999999999394 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.41456134782575393 root_relative_squared_error 1.3818711594191586 total_cost 0 unweighted_recall 0.13099999999999998 [0.985,0.03,0.09,0.18,0.025,0,0,0,0,0] area_under_roc_curve 0.52 [0.972222,0.461111,0.547222,0.583333,0.436111,0.444444,0.433333,0.444444,0.427778,0.45] area_under_roc_curve 0.5138888888888888 [0.997222,0.466667,0.488889,0.547222,0.444444,0.425,0.45,0.444444,0.436111,0.438889] area_under_roc_curve 0.5094444444444445 [0.969444,0.430556,0.425,0.575,0.469444,0.45,0.458333,0.444444,0.422222,0.45] area_under_roc_curve 0.5225 [1,0.458333,0.488889,0.586111,0.508333,0.430556,0.444444,0.444444,0.427778,0.436111] area_under_roc_curve 0.5230555555555555 [1,0.45,0.5,0.605556,0.475,0.425,0.441667,0.444444,0.444444,0.444444] area_under_roc_curve 0.5119444444444443 [1,0.463889,0.508333,0.463889,0.480556,0.447222,0.447222,0.441667,0.419444,0.447222] area_under_roc_curve 0.5038888888888888 [0.975,0.447222,0.455556,0.505556,0.455556,0.436111,0.433333,0.444444,0.441667,0.444444] area_under_roc_curve 0.5066666666666666 [1,0.475,0.491667,0.458333,0.438889,0.425,0.438889,0.444444,0.447222,0.447222] area_under_roc_curve 0.5233333333333333 [1,0.472222,0.519444,0.563889,0.458333,0.436111,0.455556,0.444444,0.433333,0.45] area_under_roc_curve 0.5219722222222222 [1,0.45,0.522222,0.569444,0.441667,0.427778,0.436111,0.45,0.475278,0.447222] 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 0.14272727272727273 [0.95,0.045455,0.181818,0.25,0,0,0,0,0,0] f_measure 0.12680988447562802 [0.97561,0.047619,0.058824,0.186047,0,0,0,0,0,0] f_measure 0.11593874078275666 [0.926829,0,0,0.232558,0,0,0,0,0,0] f_measure 0.14428933602901062 [1,0,0.058824,0.25641,0.12766,0,0,0,0,0] f_measure 0.14369963369963368 [1,0,0.1,0.285714,0.051282,0,0,0,0,0] f_measure 0.12282252564291159 [1,0.046512,0.12766,0,0.054054,0,0,0,0,0] f_measure 0.11204384587843233 [0.974359,0.040816,0,0.105263,0,0,0,0,0,0] f_measure 0.11443053070960048 [1,0.051282,0.093023,0,0,0,0,0,0,0] f_measure 0.14023008411677387 [1,0.05,0.139535,0.212766,0,0,0,0,0,0] f_measure 0.13714285714285715 [1,0,0.142857,0.228571,0,0,0,0,0,0] kappa 0.04444444444444445 kappa 0.03333333333333333 kappa 0.02222222222222221 kappa 0.04999999999999998 kappa 0.04999999999999998 kappa 0.02777777777777777 kappa 0.011111111111111105 kappa 0.016666666666666666 kappa 0.04999999999999998 kappa 0.03888888888888889 kb_relative_information_score 0.10064855811782036 kb_relative_information_score 0.09019098321221325 kb_relative_information_score 0.07973340830660586 kb_relative_information_score 0.10587734557062371 kb_relative_information_score 0.10587734557062371 kb_relative_information_score 0.08496219575940964 kb_relative_information_score 0.06927583340099872 kb_relative_information_score 0.07450462085380237 kb_relative_information_score 0.10587734557062375 kb_relative_information_score 0.10286704561398392 mean_absolute_error 0.17199999999999974 mean_absolute_error 0.17399999999999977 mean_absolute_error 0.1759999999999998 mean_absolute_error 0.17099999999999974 mean_absolute_error 0.17099999999999974 mean_absolute_error 0.1749999999999998 mean_absolute_error 0.17799999999999983 mean_absolute_error 0.17699999999999982 mean_absolute_error 0.17099999999999974 mean_absolute_error 0.1719999999999998 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 0.14724358974358975 [0.95,0.041667,0.230769,0.25,0,0,0,0,0,0] precision 0.12431771127423302 [0.952381,0.045455,0.071429,0.173913,0,0,0,0,0,0] precision 0.1122153209109731 [0.904762,0,0,0.217391,0,0,0,0,0,0] precision 0.14456975772765246 [1,0,0.071429,0.263158,0.111111,0,0,0,0,0] precision 0.14253588516746413 [1,0,0.1,0.272727,0.052632,0,0,0,0,0] precision 0.12134129013924409 [1,0.043478,0.111111,0,0.058824,0,0,0,0,0] precision 0.11455938697318008 [1,0.034483,0,0.111111,0,0,0,0,0,0] precision 0.1139588100686499 [1,0.052632,0.086957,0,0,0,0,0,0,0] precision 0.13656199677938807 [1,0.05,0.130435,0.185185,0,0,0,0,0,0] precision 0.1403030303030303 [1,0,0.136364,0.266667,0,0,0,0,0,0] predictive_accuracy 0.14 predictive_accuracy 0.13 predictive_accuracy 0.12 predictive_accuracy 0.145 predictive_accuracy 0.145 predictive_accuracy 0.125 predictive_accuracy 0.11 predictive_accuracy 0.115 predictive_accuracy 0.145 predictive_accuracy 0.135 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 0.9555555555555552 relative_absolute_error 0.9666666666666665 relative_absolute_error 0.9777777777777777 relative_absolute_error 0.9499999999999996 relative_absolute_error 0.9499999999999996 relative_absolute_error 0.9722222222222221 relative_absolute_error 0.988888888888889 relative_absolute_error 0.9833333333333334 relative_absolute_error 0.9499999999999996 relative_absolute_error 0.9555555555555554 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 0.4123442466893136 root_mean_squared_error 0.41412558481697265 root_mean_squared_error 0.4177319714841081 root_mean_squared_error 0.41082572677204315 root_mean_squared_error 0.41140004861448387 root_mean_squared_error 0.4162331077653479 root_mean_squared_error 0.42015208886518407 root_mean_squared_error 0.41892720131306793 root_mean_squared_error 0.41170377700477767 root_mean_squared_error 0.4120409904096648 root_relative_squared_error 1.3744808222977127 root_relative_squared_error 1.3804186160565763 root_relative_squared_error 1.3924399049470282 root_relative_squared_error 1.3694190892401448 root_relative_squared_error 1.3713334953816139 root_relative_squared_error 1.3874436925511602 root_relative_squared_error 1.400506962883948 root_relative_squared_error 1.3964240043768938 root_relative_squared_error 1.3723459233492596 root_relative_squared_error 1.3734699680322169 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 0.13999999999999999 [0.95,0.05,0.15,0.25,0,0,0,0,0,0] unweighted_recall 0.13 [1,0.05,0.05,0.2,0,0,0,0,0,0] unweighted_recall 0.12 [0.95,0,0,0.25,0,0,0,0,0,0] unweighted_recall 0.145 [1,0,0.05,0.25,0.15,0,0,0,0,0] unweighted_recall 0.14500000000000002 [1,0,0.1,0.3,0.05,0,0,0,0,0] unweighted_recall 0.125 [1,0.05,0.15,0,0.05,0,0,0,0,0] unweighted_recall 0.11000000000000001 [0.95,0.05,0,0.1,0,0,0,0,0,0] unweighted_recall 0.11500000000000002 [1,0.05,0.1,0,0,0,0,0,0,0] unweighted_recall 0.145 [1,0.05,0.15,0.25,0,0,0,0,0,0] unweighted_recall 0.13499999999999998 [1,0,0.15,0.2,0,0,0,0,0,0] usercpu_time_millis 31.25 usercpu_time_millis 0 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 0 usercpu_time_millis 0 usercpu_time_millis 0 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_training 31.25 usercpu_time_millis_training 0 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 usercpu_time_millis_training 0 usercpu_time_millis_training 0 usercpu_time_millis_training 0 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 wall_clock_time_millis 20.987272262573242 wall_clock_time_millis 9.994029998779297 wall_clock_time_millis 9.994268417358398 wall_clock_time_millis 10.993480682373047 wall_clock_time_millis 9.99307632446289 wall_clock_time_millis 10.972738265991211 wall_clock_time_millis 11.012554168701172 wall_clock_time_millis 9.993553161621094 wall_clock_time_millis 10.993003845214844 wall_clock_time_millis 9.994029998779297 wall_clock_time_millis_testing 0.9999275207519531 wall_clock_time_millis_testing 1.0006427764892578 wall_clock_time_millis_testing 1.0004043579101562 wall_clock_time_millis_testing 1.001119613647461 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0.9999275207519531 wall_clock_time_millis_testing 0.99945068359375 wall_clock_time_millis_testing 0.9989738464355469 wall_clock_time_millis_testing 0 wall_clock_time_millis_training 19.98734474182129 wall_clock_time_millis_training 8.993387222290039 wall_clock_time_millis_training 8.993864059448242 wall_clock_time_millis_training 9.992361068725586 wall_clock_time_millis_training 9.99307632446289 wall_clock_time_millis_training 10.972738265991211 wall_clock_time_millis_training 10.012626647949219 wall_clock_time_millis_training 8.994102478027344 wall_clock_time_millis_training 9.994029998779297 wall_clock_time_millis_training 9.994029998779297 weighted_recall 0.14 [0.95,0.05,0.15,0.25,0,0,0,0,0,0] weighted_recall 0.13 [1,0.05,0.05,0.2,0,0,0,0,0,0] weighted_recall 0.12 [0.95,0,0,0.25,0,0,0,0,0,0] weighted_recall 0.145 [1,0,0.05,0.25,0.15,0,0,0,0,0] weighted_recall 0.145 [1,0,0.1,0.3,0.05,0,0,0,0,0] weighted_recall 0.125 [1,0.05,0.15,0,0.05,0,0,0,0,0] weighted_recall 0.11 [0.95,0.05,0,0.1,0,0,0,0,0,0] weighted_recall 0.115 [1,0.05,0.1,0,0,0,0,0,0,0] weighted_recall 0.145 [1,0.05,0.15,0.25,0,0,0,0,0,0] weighted_recall 0.135 [1,0,0.15,0.2,0,0,0,0,0,0]