10588219 32117 VAIBHAV JAISWAL 18 Supervised Classification 19167 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.ensemble._forest.RandomForestClassifier)(1) 8304105 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 bootstrap true 19095 ccp_alpha 0.0 19095 class_weight null 19095 criterion "gini" 19095 max_depth null 19095 max_features "auto" 19095 max_leaf_nodes null 19095 max_samples null 19095 min_impurity_decrease 0.0 19095 min_samples_leaf 1 19095 min_samples_split 2 19095 min_weight_fraction_leaf 0.0 19095 n_estimators 100 19095 n_jobs null 19095 oob_score false 19095 random_state 0 19095 verbose 0 19095 warm_start false 19095 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 19167 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"}}] 19167 verbose false 19167 openml-python Sklearn_1.0.2. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22104005 description https://api.openml.org/data/download/22104005/description.xml -1 22104006 predictions https://api.openml.org/data/download/22104006/predictions.arff area_under_roc_curve 0.5080723611111112 [0.999743,0.362731,0.580451,0.679549,0.49301,0.382733,0.352926,0.42829,0.391518,0.409772] average_cost 0 f_measure 0.12623571730778108 [0.98995,0.004866,0.113695,0.148883,0,0,0,0,0.004963,0] kappa 0.02833333333333333 kb_relative_information_score 0.09998527186530887 mean_absolute_error 0.17375446666666233 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.1255 [0.985,0.005,0.11,0.15,0,0,0,0,0.005,0] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.12700452498718268 [0.994949,0.004739,0.117647,0.147783,0,0,0,0,0.004926,0] predictive_accuracy 0.1255 prior_entropy 3.3219280948872383 relative_absolute_error 0.9653025925925387 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.3810950196055269 root_relative_squared_error 1.2703167320184037 total_cost 0 unweighted_recall 0.1255 [0.985,0.005,0.11,0.15,0,0,0,0,0.005,0] area_under_roc_curve 0.5187361111111112 [0.999583,0.367778,0.587222,0.75625,0.499583,0.388472,0.363611,0.427778,0.416528,0.380556] area_under_roc_curve 0.5079305555555556 [1,0.353194,0.628611,0.683056,0.515,0.363889,0.327778,0.425,0.368333,0.414444] area_under_roc_curve 0.49958333333333343 [0.999444,0.315972,0.4925,0.690833,0.481667,0.425694,0.362917,0.446667,0.379861,0.400278] area_under_roc_curve 0.5088194444444443 [1,0.369583,0.541667,0.716528,0.507222,0.35,0.362917,0.425,0.38,0.435278] area_under_roc_curve 0.5133194444444444 [1,0.374444,0.597361,0.72875,0.48875,0.406806,0.319444,0.419444,0.382639,0.415556] area_under_roc_curve 0.5109027777777778 [1,0.352222,0.654583,0.564444,0.580972,0.369444,0.355556,0.425,0.398472,0.408333] area_under_roc_curve 0.5079583333333333 [0.998472,0.345972,0.644167,0.634861,0.497778,0.375,0.382917,0.416667,0.383056,0.400694] area_under_roc_curve 0.5034166666666667 [1,0.377222,0.549028,0.663472,0.430278,0.372361,0.361111,0.438889,0.441806,0.4] area_under_roc_curve 0.5175277777777777 [1,0.443472,0.615417,0.728611,0.454028,0.375694,0.325,0.433333,0.372361,0.427361] area_under_roc_curve 0.4950833333333334 [1,0.325139,0.506806,0.637639,0.477083,0.399861,0.368056,0.425,0.395833,0.415417] 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 0.13312267535630823 [0.974359,0,0.210526,0.146341,0,0,0,0,0,0] f_measure 0.11664266911005425 [0.97561,0,0.051282,0.139535,0,0,0,0,0,0] f_measure 0.12172161172161172 [0.974359,0,0.1,0.142857,0,0,0,0,0,0] f_measure 0.12642857142857142 [1,0,0.114286,0.15,0,0,0,0,0,0] f_measure 0.13551282051282051 [1,0,0.15,0.205128,0,0,0,0,0,0] f_measure 0.12127659574468085 [1,0,0.212766,0,0,0,0,0,0,0] f_measure 0.11243589743589742 [0.974359,0,0,0.15,0,0,0,0,0,0] f_measure 0.11552631578947369 [1,0,0.05,0.105263,0,0,0,0,0,0] f_measure 0.13581252783526762 [1,0.04878,0.105263,0.204082,0,0,0,0,0,0] f_measure 0.1381482322658793 [1,0,0.117647,0.216216,0,0,0,0,0.047619,0] kappa 0.03333333333333333 kappa 0.02222222222222221 kappa 0.02222222222222221 kappa 0.02777777777777777 kappa 0.03888888888888889 kappa 0.02777777777777777 kappa 0.011111111111111105 kappa 0.016666666666666666 kappa 0.04444444444444445 kappa 0.03888888888888889 kb_relative_information_score 0.10188713152310011 kb_relative_information_score 0.10038782339001916 kb_relative_information_score 0.09015574439136018 kb_relative_information_score 0.09876935552157336 kb_relative_information_score 0.10775281032569663 kb_relative_information_score 0.09997457993196802 kb_relative_information_score 0.08420850440163383 kb_relative_information_score 0.09407246007550318 kb_relative_information_score 0.11652263126346254 kb_relative_information_score 0.10612167782873509 mean_absolute_error 0.17378999999999992 mean_absolute_error 0.1736299999999999 mean_absolute_error 0.17577999999999988 mean_absolute_error 0.1736866666666666 mean_absolute_error 0.17226499999999992 mean_absolute_error 0.17383966666666656 mean_absolute_error 0.17589749999999993 mean_absolute_error 0.17486999999999994 mean_absolute_error 0.17078999999999983 mean_absolute_error 0.1729958333333332 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 0.1365079365079365 [1,0,0.222222,0.142857,0,0,0,0,0,0] precision 0.11354473139370165 [0.952381,0,0.052632,0.130435,0,0,0,0,0,0] precision 0.12363636363636363 [1,0,0.1,0.136364,0,0,0,0,0,0] precision 0.12833333333333333 [1,0,0.133333,0.15,0,0,0,0,0,0] precision 0.13605263157894737 [1,0,0.15,0.210526,0,0,0,0,0,0] precision 0.11851851851851851 [1,0,0.185185,0,0,0,0,0,0,0] precision 0.115 [1,0,0,0.15,0,0,0,0,0,0] precision 0.11611111111111111 [1,0,0.05,0.111111,0,0,0,0,0,0] precision 0.13311439518336068 [1,0.047619,0.111111,0.172414,0,0,0,0,0,0] precision 0.14236058059587473 [1,0,0.142857,0.235294,0,0,0,0,0.045455,0] predictive_accuracy 0.13 predictive_accuracy 0.12 predictive_accuracy 0.12 predictive_accuracy 0.125 predictive_accuracy 0.135 predictive_accuracy 0.125 predictive_accuracy 0.11 predictive_accuracy 0.115 predictive_accuracy 0.14 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 0.9655000000000006 relative_absolute_error 0.9646111111111115 relative_absolute_error 0.9765555555555561 relative_absolute_error 0.9649259259259266 relative_absolute_error 0.9570277777777784 relative_absolute_error 0.9657759259259264 relative_absolute_error 0.977208333333334 relative_absolute_error 0.9715000000000008 relative_absolute_error 0.9488333333333334 relative_absolute_error 0.9610879629629633 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 0.38157050949194327 root_mean_squared_error 0.3803054008058341 root_mean_squared_error 0.3827557088861626 root_mean_squared_error 0.3814450206827735 root_mean_squared_error 0.3816681336433573 root_mean_squared_error 0.38055155861035556 root_mean_squared_error 0.38730958700293233 root_mean_squared_error 0.38022463707062365 root_mean_squared_error 0.37530211422262505 root_mean_squared_error 0.3797136168710592 root_relative_squared_error 1.2719016983064784 root_relative_squared_error 1.267684669352781 root_relative_squared_error 1.275852362953876 root_relative_squared_error 1.2714834022759123 root_relative_squared_error 1.2722271121445252 root_relative_squared_error 1.2685051953678528 root_relative_squared_error 1.291031956676442 root_relative_squared_error 1.2674154569020795 root_relative_squared_error 1.251007047408751 root_relative_squared_error 1.2657120562368647 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 0.12999999999999998 [0.95,0,0.2,0.15,0,0,0,0,0,0] unweighted_recall 0.12 [1,0,0.05,0.15,0,0,0,0,0,0] unweighted_recall 0.12 [0.95,0,0.1,0.15,0,0,0,0,0,0] unweighted_recall 0.125 [1,0,0.1,0.15,0,0,0,0,0,0] unweighted_recall 0.13499999999999998 [1,0,0.15,0.2,0,0,0,0,0,0] unweighted_recall 0.125 [1,0,0.25,0,0,0,0,0,0,0] unweighted_recall 0.10999999999999999 [0.95,0,0,0.15,0,0,0,0,0,0] unweighted_recall 0.11500000000000002 [1,0,0.05,0.1,0,0,0,0,0,0] unweighted_recall 0.14 [1,0.05,0.1,0.25,0,0,0,0,0,0] unweighted_recall 0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0] usercpu_time_millis 406.25 usercpu_time_millis 359.375 usercpu_time_millis 359.375 usercpu_time_millis 359.375 usercpu_time_millis 390.625 usercpu_time_millis 359.375 usercpu_time_millis 359.375 usercpu_time_millis 375 usercpu_time_millis 359.375 usercpu_time_millis 375 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_training 390.625 usercpu_time_millis_training 343.75 usercpu_time_millis_training 343.75 usercpu_time_millis_training 343.75 usercpu_time_millis_training 375 usercpu_time_millis_training 343.75 usercpu_time_millis_training 343.75 usercpu_time_millis_training 359.375 usercpu_time_millis_training 343.75 usercpu_time_millis_training 359.375 wall_clock_time_millis 406.7685604095459 wall_clock_time_millis 368.76654624938965 wall_clock_time_millis 351.8202304840088 wall_clock_time_millis 357.79428482055664 wall_clock_time_millis 382.7798366546631 wall_clock_time_millis 355.79514503479004 wall_clock_time_millis 360.77094078063965 wall_clock_time_millis 363.8110160827637 wall_clock_time_millis 354.7952175140381 wall_clock_time_millis 372.7850914001465 wall_clock_time_millis_testing 18.98980140686035 wall_clock_time_millis_testing 16.99042320251465 wall_clock_time_millis_testing 16.988754272460938 wall_clock_time_millis_testing 16.99042320251465 wall_clock_time_millis_testing 16.989469528198242 wall_clock_time_millis_testing 16.989469528198242 wall_clock_time_millis_testing 16.990184783935547 wall_clock_time_millis_testing 16.990184783935547 wall_clock_time_millis_testing 16.99376106262207 wall_clock_time_millis_testing 16.990184783935547 wall_clock_time_millis_training 387.77875900268555 wall_clock_time_millis_training 351.776123046875 wall_clock_time_millis_training 334.83147621154785 wall_clock_time_millis_training 340.803861618042 wall_clock_time_millis_training 365.79036712646484 wall_clock_time_millis_training 338.8056755065918 wall_clock_time_millis_training 343.7807559967041 wall_clock_time_millis_training 346.8208312988281 wall_clock_time_millis_training 337.801456451416 wall_clock_time_millis_training 355.79490661621094 weighted_recall 0.13 [0.95,0,0.2,0.15,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0.05,0.15,0,0,0,0,0,0] weighted_recall 0.12 [0.95,0,0.1,0.15,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.1,0.15,0,0,0,0,0,0] weighted_recall 0.135 [1,0,0.15,0.2,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.25,0,0,0,0,0,0,0] weighted_recall 0.11 [0.95,0,0,0.15,0,0,0,0,0,0] weighted_recall 0.115 [1,0,0.05,0.1,0,0,0,0,0,0] weighted_recall 0.14 [1,0.05,0.1,0.25,0,0,0,0,0,0] weighted_recall 0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]