10588229 32117 VAIBHAV JAISWAL 18 Supervised Classification 19170 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.ensemble._gb.GradientBoostingClassifier)(1) 8304107 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 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 19170 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"}}] 19170 verbose false 19170 ccp_alpha 0.0 19171 criterion "friedman_mse" 19171 init null 19171 learning_rate 0.1 19171 loss "deviance" 19171 max_depth 3 19171 max_features null 19171 max_leaf_nodes null 19171 min_impurity_decrease 0.0 19171 min_samples_leaf 1 19171 min_samples_split 2 19171 min_weight_fraction_leaf 0.0 19171 n_estimators 100 19171 n_iter_no_change null 19171 random_state 0 19171 subsample 1.0 19171 tol 0.0001 19171 validation_fraction 0.1 19171 verbose 0 19171 warm_start false 19171 openml-python Sklearn_1.0.2. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22104025 description https://api.openml.org/data/download/22104025/description.xml -1 22104026 predictions https://api.openml.org/data/download/22104026/predictions.arff area_under_roc_curve 0.5469225 [0.993408,0.358353,0.675,0.731172,0.604872,0.425875,0.552601,0.379603,0.147186,0.601154] average_cost 0 f_measure 0.12562792079498522 [0.992443,0.004843,0.087629,0.150852,0,0,0,0,0.020513,0] kappa 0.02777777777777777 kb_relative_information_score 0.09834348371988005 mean_absolute_error 0.17368948235707685 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.125 [0.985,0.005,0.085,0.155,0,0,0,0,0.02,0] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.12630924304542132 [1,0.004695,0.090426,0.146919,0,0,0,0,0.021053,0] predictive_accuracy 0.125 prior_entropy 3.3219280948872383 relative_absolute_error 0.9649415686503972 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.3844812576648142 root_relative_squared_error 1.2816041922160277 total_cost 0 unweighted_recall 0.125 [0.985,0.005,0.085,0.155,0,0,0,0,0.02,0] area_under_roc_curve 0.544 [0.998611,0.324722,0.674167,0.753611,0.608333,0.403889,0.588333,0.373611,0.155,0.559722] area_under_roc_curve 0.5484166666666667 [1,0.3475,0.715,0.758889,0.634444,0.39,0.507639,0.426389,0.056667,0.647639] area_under_roc_curve 0.5498611111111111 [0.982222,0.362222,0.64,0.733611,0.608611,0.455833,0.57625,0.436667,0.155278,0.547917] area_under_roc_curve 0.5388055555555554 [1,0.353333,0.600833,0.689167,0.583611,0.486389,0.512361,0.365,0.182778,0.614583] area_under_roc_curve 0.5535555555555556 [1,0.435556,0.619167,0.743333,0.665278,0.485278,0.500556,0.355,0.148056,0.583333] area_under_roc_curve 0.5587777777777778 [1,0.338056,0.713333,0.709722,0.643333,0.445,0.590139,0.328889,0.183611,0.635694] area_under_roc_curve 0.5192777777777777 [0.987778,0.341944,0.683889,0.679722,0.564167,0.24,0.573472,0.374722,0.121389,0.625694] area_under_roc_curve 0.5496111111111112 [1,0.349167,0.696944,0.780833,0.605833,0.412222,0.566806,0.291667,0.2075,0.585139] area_under_roc_curve 0.5601666666666666 [1,0.371389,0.686389,0.7325,0.580556,0.472222,0.556111,0.341667,0.229167,0.631667] area_under_roc_curve 0.5458333333333334 [1,0.368889,0.699167,0.735833,0.561111,0.400556,0.567083,0.416667,0.109722,0.599306] 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 0.13245641727173874 [0.974359,0,0.117647,0.232558,0,0,0,0,0,0] f_measure 0.12428571428571429 [1,0,0.142857,0.1,0,0,0,0,0,0] f_measure 0.11659966050209952 [0.974359,0,0.04878,0.142857,0,0,0,0,0,0] f_measure 0.11992921492921493 [1,0,0.054054,0.095238,0,0,0,0,0.05,0] f_measure 0.13383838383838384 [1,0,0.111111,0.227273,0,0,0,0,0,0] f_measure 0.11333333333333333 [1,0,0.133333,0,0,0,0,0,0,0] f_measure 0.11743589743589743 [0.974359,0,0,0.2,0,0,0,0,0,0] f_measure 0.1233108108108108 [1,0,0,0.108108,0,0,0,0,0.125,0] f_measure 0.14150085579803168 [1,0.04878,0.157895,0.208333,0,0,0,0,0,0] f_measure 0.13137426900584795 [1,0,0.111111,0.15,0,0,0,0,0.052632,0] kappa 0.03333333333333333 kappa 0.02777777777777777 kappa 0.016666666666666666 kappa 0.02222222222222221 kappa 0.03888888888888889 kappa 0.016666666666666666 kappa 0.016666666666666666 kappa 0.02222222222222221 kappa 0.04999999999999998 kappa 0.03333333333333333 kb_relative_information_score 0.10243666512437354 kb_relative_information_score 0.10369863426944624 kb_relative_information_score 0.08955292046618349 kb_relative_information_score 0.09133260012157042 kb_relative_information_score 0.10526259704290056 kb_relative_information_score 0.09100446384083064 kb_relative_information_score 0.08718367965419115 kb_relative_information_score 0.09490301151845898 kb_relative_information_score 0.10926603052477242 kb_relative_information_score 0.1087942346360379 mean_absolute_error 0.1730280238616568 mean_absolute_error 0.1731050685004983 mean_absolute_error 0.17544479665367024 mean_absolute_error 0.1747922286476437 mean_absolute_error 0.17236873222958007 mean_absolute_error 0.17493603293586826 mean_absolute_error 0.1758948740881162 mean_absolute_error 0.17407574497560802 mean_absolute_error 0.1713135746812517 mean_absolute_error 0.17193574699687697 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 0.1360248447204969 [1,0,0.142857,0.217391,0,0,0,0,0,0] precision 0.12363636363636363 [1,0,0.136364,0.1,0,0,0,0,0,0] precision 0.11839826839826839 [1,0,0.047619,0.136364,0,0,0,0,0,0] precision 0.11997326203208555 [1,0,0.058824,0.090909,0,0,0,0,0.05,0] precision 0.13333333333333333 [1,0,0.125,0.208333,0,0,0,0,0,0] precision 0.11199999999999999 [1,0,0.12,0,0,0,0,0,0,0] precision 0.12 [1,0,0,0.2,0,0,0,0,0,0] precision 0.1284313725490196 [1,0,0,0.117647,0,0,0,0,0.166667,0] precision 0.1392857142857143 [1,0.047619,0.166667,0.178571,0,0,0,0,0,0] precision 0.13305555555555557 [1,0,0.125,0.15,0,0,0,0,0.055556,0] predictive_accuracy 0.13 predictive_accuracy 0.125 predictive_accuracy 0.115 predictive_accuracy 0.12 predictive_accuracy 0.135 predictive_accuracy 0.115 predictive_accuracy 0.115 predictive_accuracy 0.12 predictive_accuracy 0.145 predictive_accuracy 0.13 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 0.9612667992314278 relative_absolute_error 0.9616948250027694 relative_absolute_error 0.9746933147426136 relative_absolute_error 0.971067936931355 relative_absolute_error 0.9576040679421125 relative_absolute_error 0.9718668496437136 relative_absolute_error 0.9771937449339798 relative_absolute_error 0.9670874720867123 relative_absolute_error 0.9517420815625105 relative_absolute_error 0.9551985944270954 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 0.3853083200870276 root_mean_squared_error 0.3841143163745166 root_mean_squared_error 0.3853101528839844 root_mean_squared_error 0.38617429927782404 root_mean_squared_error 0.384115129316021 root_mean_squared_error 0.3859548023527346 root_mean_squared_error 0.3893087576908628 root_mean_squared_error 0.3820467413844243 root_mean_squared_error 0.37975853392838 root_mean_squared_error 0.3826414176582701 root_relative_squared_error 1.2843610669567593 root_relative_squared_error 1.2803810545817225 root_relative_squared_error 1.284367176279949 root_relative_squared_error 1.2872476642594142 root_relative_squared_error 1.2803837643867373 root_relative_squared_error 1.2865160078424496 root_relative_squared_error 1.2976958589695438 root_relative_squared_error 1.2734891379480817 root_relative_squared_error 1.2658617797612672 root_relative_squared_error 1.2754713921942342 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 0.13 [0.95,0,0.1,0.25,0,0,0,0,0,0] unweighted_recall 0.125 [1,0,0.15,0.1,0,0,0,0,0,0] unweighted_recall 0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0] unweighted_recall 0.12000000000000002 [1,0,0.05,0.1,0,0,0,0,0.05,0] unweighted_recall 0.135 [1,0,0.1,0.25,0,0,0,0,0,0] unweighted_recall 0.11499999999999999 [1,0,0.15,0,0,0,0,0,0,0] unweighted_recall 0.11499999999999999 [0.95,0,0,0.2,0,0,0,0,0,0] unweighted_recall 0.12000000000000002 [1,0,0,0.1,0,0,0,0,0.1,0] unweighted_recall 0.145 [1,0.05,0.15,0.25,0,0,0,0,0,0] unweighted_recall 0.13 [1,0,0.1,0.15,0,0,0,0,0.05,0] usercpu_time_millis 3156.25 usercpu_time_millis 3125 usercpu_time_millis 3140.625 usercpu_time_millis 3109.375 usercpu_time_millis 3156.25 usercpu_time_millis 3140.625 usercpu_time_millis 3171.875 usercpu_time_millis 3125 usercpu_time_millis 3140.625 usercpu_time_millis 3140.625 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 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_training 3156.25 usercpu_time_millis_training 3125 usercpu_time_millis_training 3140.625 usercpu_time_millis_training 3109.375 usercpu_time_millis_training 3156.25 usercpu_time_millis_training 3140.625 usercpu_time_millis_training 3156.25 usercpu_time_millis_training 3109.375 usercpu_time_millis_training 3125 usercpu_time_millis_training 3140.625 wall_clock_time_millis 3149.1947174072266 wall_clock_time_millis 3118.2336807250977 wall_clock_time_millis 3142.176866531372 wall_clock_time_millis 3143.197536468506 wall_clock_time_millis 3161.1900329589844 wall_clock_time_millis 3140.178442001343 wall_clock_time_millis 3165.2047634124756 wall_clock_time_millis 3120.210647583008 wall_clock_time_millis 3134.2031955718994 wall_clock_time_millis 3142.220973968506 wall_clock_time_millis_testing 3.997325897216797 wall_clock_time_millis_testing 3.9968490600585938 wall_clock_time_millis_testing 4.992485046386719 wall_clock_time_millis_testing 3.9975643157958984 wall_clock_time_millis_testing 3.997325897216797 wall_clock_time_millis_testing 3.9968490600585938 wall_clock_time_millis_testing 3.9980411529541016 wall_clock_time_millis_testing 3.9975643157958984 wall_clock_time_millis_testing 3.997802734375 wall_clock_time_millis_testing 3.997802734375 wall_clock_time_millis_training 3145.1973915100098 wall_clock_time_millis_training 3114.236831665039 wall_clock_time_millis_training 3137.1843814849854 wall_clock_time_millis_training 3139.19997215271 wall_clock_time_millis_training 3157.1927070617676 wall_clock_time_millis_training 3136.181592941284 wall_clock_time_millis_training 3161.2067222595215 wall_clock_time_millis_training 3116.213083267212 wall_clock_time_millis_training 3130.2053928375244 wall_clock_time_millis_training 3138.223171234131 weighted_recall 0.13 [0.95,0,0.1,0.25,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.15,0.1,0,0,0,0,0,0] weighted_recall 0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0.05,0.1,0,0,0,0,0.05,0] weighted_recall 0.135 [1,0,0.1,0.25,0,0,0,0,0,0] weighted_recall 0.115 [1,0,0.15,0,0,0,0,0,0,0] weighted_recall 0.115 [0.95,0,0,0.2,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0,0.1,0,0,0,0,0.1,0] weighted_recall 0.145 [1,0.05,0.15,0.25,0,0,0,0,0,0] weighted_recall 0.13 [1,0,0.1,0.15,0,0,0,0,0.05,0]