10588178 32117 VAIBHAV JAISWAL 18 Supervised Classification 19159 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.linear_model._stochastic_gradient.SGDClassifier)(1) 8304102 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 19159 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"}}] 19159 verbose false 19159 alpha 0.0001 19160 average false 19160 class_weight null 19160 early_stopping false 19160 epsilon 0.1 19160 eta0 0.0 19160 fit_intercept true 19160 l1_ratio 0.15 19160 learning_rate "optimal" 19160 loss "hinge" 19160 max_iter 1000 19160 n_iter_no_change 5 19160 n_jobs null 19160 penalty "l2" 19160 power_t 0.5 19160 random_state 0 19160 shuffle true 19160 tol 0.001 19160 validation_fraction 0.1 19160 verbose 0 19160 warm_start false 19160 openml-python Sklearn_1.0.2. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22103923 description https://api.openml.org/data/download/22103923/description.xml -1 22103924 predictions https://api.openml.org/data/download/22103924/predictions.arff area_under_roc_curve 0.5155555555555555 [0.9925,0.444722,0.508611,0.539444,0.455278,0.4375,0.451667,0.442222,0.433056,0.450556] average_cost 0 f_measure 0.1309826604879671 [0.992443,0.00489,0.10585,0.168478,0.015345,0.008989,0,0,0.008677,0.005155] kappa 0.031111111111111107 kb_relative_information_score 0.08809946823109545 mean_absolute_error 0.17439999999999437 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.128 [0.985,0.005,0.095,0.155,0.015,0.01,0,0,0.01,0.005] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.13456574096389942 [1,0.004785,0.119497,0.184524,0.015707,0.008163,0,0,0.007663,0.005319] predictive_accuracy 0.128 prior_entropy 3.3219280948872383 relative_absolute_error 0.9688888888888277 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.41761226035641524 root_relative_squared_error 1.3920408678546963 total_cost 0 unweighted_recall 0.12799999999999997 [0.985,0.005,0.095,0.155,0.015,0.01,0,0,0.01,0.005] area_under_roc_curve 0.5194444444444444 [0.975,0.461111,0.561111,0.555556,0.441667,0.380556,0.438889,0.444444,0.494444,0.441667] area_under_roc_curve 0.5138888888888887 [1,0.441667,0.488889,0.555556,0.461111,0.477778,0.436111,0.438889,0.397222,0.441667] area_under_roc_curve 0.5083333333333333 [0.975,0.430556,0.444444,0.533333,0.483333,0.483333,0.455556,0.444444,0.394444,0.438889] area_under_roc_curve 0.5138888888888888 [1,0.45,0.497222,0.480556,0.472222,0.475,0.461111,0.438889,0.419444,0.444444] area_under_roc_curve 0.525 [1,0.494444,0.6,0.511111,0.433333,0.397222,0.45,0.438889,0.472222,0.452778] area_under_roc_curve 0.5111111111111112 [1,0.455556,0.513889,0.486111,0.463889,0.386111,0.444444,0.441667,0.463889,0.455556] area_under_roc_curve 0.5055555555555555 [0.975,0.447222,0.436111,0.533333,0.458333,0.380556,0.438889,0.444444,0.488889,0.452778] area_under_roc_curve 0.5111111111111111 [1,0.444444,0.491667,0.525,0.427778,0.511111,0.444444,0.447222,0.366667,0.452778] area_under_roc_curve 0.5388888888888889 [1,0.436111,0.536111,0.694444,0.452778,0.497222,0.463889,0.444444,0.388889,0.475] area_under_roc_curve 0.5083333333333333 [1,0.386111,0.516667,0.519444,0.458333,0.386111,0.483333,0.438889,0.444444,0.45] 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 0.1416041948918661 [0.974359,0,0.214286,0.2,0,0.027397,0,0,0,0] f_measure 0.12298507462686567 [1,0,0,0.2,0,0,0,0,0.029851,0] f_measure 0.11722537112010796 [0.974359,0,0.04,0.157895,0,0,0,0,0,0] f_measure 0.12324684881710578 [1,0,0.064516,0.054054,0.08,0,0,0,0.033898,0] f_measure 0.137037037037037 [1,0,0.259259,0.111111,0,0,0,0,0,0] f_measure 0.11904761904761903 [1,0,0.133333,0.057143,0,0,0,0,0,0] f_measure 0.11616605616605616 [0.974359,0,0,0.142857,0.044444,0,0,0,0,0] f_measure 0.1223264540337711 [1,0,0,0.146341,0,0.076923,0,0,0,0] f_measure 0.1637166048486803 [1,0.037736,0.148148,0.4,0,0,0,0,0,0.051282] f_measure 0.12046035805626598 [1,0,0.117647,0.086957,0,0,0,0,0,0] kappa 0.03888888888888889 kappa 0.02777777777777777 kappa 0.016666666666666666 kappa 0.02777777777777777 kappa 0.04999999999999998 kappa 0.02222222222222221 kappa 0.011111111111111105 kappa 0.02222222222222221 kappa 0.07777777777777778 kappa 0.016666666666666666 kb_relative_information_score 0.09541977066501695 kb_relative_information_score 0.0849621957594095 kb_relative_information_score 0.07450462085380219 kb_relative_information_score 0.08496219575940904 kb_relative_information_score 0.1058773455706238 kb_relative_information_score 0.07973340830660601 kb_relative_information_score 0.06927583340099874 kb_relative_information_score 0.07973340830660595 kb_relative_information_score 0.1320212828346407 kb_relative_information_score 0.07450462085380236 mean_absolute_error 0.17299999999999977 mean_absolute_error 0.1749999999999998 mean_absolute_error 0.17699999999999982 mean_absolute_error 0.1749999999999998 mean_absolute_error 0.17099999999999974 mean_absolute_error 0.1759999999999998 mean_absolute_error 0.17799999999999983 mean_absolute_error 0.1759999999999998 mean_absolute_error 0.16599999999999965 mean_absolute_error 0.17699999999999982 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 0.1593867924528302 [1,0,0.375,0.2,0,0.018868,0,0,0,0] precision 0.12212765957446808 [1,0,0,0.2,0,0,0,0,0.021277,0] precision 0.12 [1,0,0.033333,0.166667,0,0,0,0,0,0] precision 0.12420403126285479 [1,0,0.090909,0.058824,0.066667,0,0,0,0.025641,0] precision 0.13308823529411765 [1,0,0.205882,0.125,0,0,0,0,0,0] precision 0.11866666666666666 [1,0,0.12,0.066667,0,0,0,0,0,0] precision 0.129 [1,0,0,0.25,0.04,0,0,0,0,0] precision 0.13095238095238096 [1,0,0,0.142857,0,0.166667,0,0,0,0] precision 0.17019822282980177 [1,0.030303,0.285714,0.333333,0,0,0,0,0,0.052632] precision 0.14761904761904762 [1,0,0.142857,0.333333,0,0,0,0,0,0] predictive_accuracy 0.135 predictive_accuracy 0.125 predictive_accuracy 0.115 predictive_accuracy 0.125 predictive_accuracy 0.145 predictive_accuracy 0.12 predictive_accuracy 0.11 predictive_accuracy 0.12 predictive_accuracy 0.17 predictive_accuracy 0.115 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 0.9611111111111108 relative_absolute_error 0.9722222222222221 relative_absolute_error 0.9833333333333334 relative_absolute_error 0.9722222222222221 relative_absolute_error 0.9499999999999996 relative_absolute_error 0.9777777777777777 relative_absolute_error 0.988888888888889 relative_absolute_error 0.9777777777777777 relative_absolute_error 0.9222222222222213 relative_absolute_error 0.9833333333333334 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 0.41593268686170815 root_mean_squared_error 0.4183300132670375 root_mean_squared_error 0.42071367935925236 root_mean_squared_error 0.4183300132670375 root_mean_squared_error 0.41352146256270633 root_mean_squared_error 0.41952353926806035 root_mean_squared_error 0.4219004621945795 root_mean_squared_error 0.41952353926806035 root_mean_squared_error 0.40743097574926684 root_mean_squared_error 0.42071367935925236 root_relative_squared_error 1.386442289539028 root_relative_squared_error 1.3944333775567928 root_relative_squared_error 1.4023789311975088 root_relative_squared_error 1.3944333775567928 root_relative_squared_error 1.378404875209022 root_relative_squared_error 1.3984117975602017 root_relative_squared_error 1.4063348739819324 root_relative_squared_error 1.3984117975602017 root_relative_squared_error 1.358103252497557 root_relative_squared_error 1.4023789311975088 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 0.13499999999999998 [0.95,0,0.15,0.2,0,0.05,0,0,0,0] unweighted_recall 0.125 [1,0,0,0.2,0,0,0,0,0.05,0] unweighted_recall 0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0] unweighted_recall 0.12500000000000003 [1,0,0.05,0.05,0.1,0,0,0,0.05,0] unweighted_recall 0.14500000000000002 [1,0,0.35,0.1,0,0,0,0,0,0] unweighted_recall 0.12 [1,0,0.15,0.05,0,0,0,0,0,0] unweighted_recall 0.11000000000000001 [0.95,0,0,0.1,0.05,0,0,0,0,0] unweighted_recall 0.12 [1,0,0,0.15,0,0.05,0,0,0,0] unweighted_recall 0.17 [1,0.05,0.1,0.5,0,0,0,0,0,0.05] unweighted_recall 0.11500000000000002 [1,0,0.1,0.05,0,0,0,0,0,0] usercpu_time_millis 46.875 usercpu_time_millis 46.875 usercpu_time_millis 46.875 usercpu_time_millis 62.5 usercpu_time_millis 46.875 usercpu_time_millis 46.875 usercpu_time_millis 46.875 usercpu_time_millis 46.875 usercpu_time_millis 46.875 usercpu_time_millis 31.25 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 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 62.5 usercpu_time_millis_training 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 31.25 wall_clock_time_millis 42.97447204589844 wall_clock_time_millis 48.94852638244629 wall_clock_time_millis 55.96733093261719 wall_clock_time_millis 55.98807334899902 wall_clock_time_millis 48.97284507751465 wall_clock_time_millis 43.951988220214844 wall_clock_time_millis 43.9755916595459 wall_clock_time_millis 43.97463798522949 wall_clock_time_millis 45.95065116882324 wall_clock_time_millis 39.97635841369629 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 1.0004043579101562 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 1.0013580322265625 wall_clock_time_millis_testing 0.9999275207519531 wall_clock_time_millis_testing 1.0008811950683594 wall_clock_time_millis_testing 0.9999275207519531 wall_clock_time_millis_testing 0.9999275207519531 wall_clock_time_millis_testing 0.9999275207519531 wall_clock_time_millis_training 42.97447204589844 wall_clock_time_millis_training 47.94812202453613 wall_clock_time_millis_training 55.96733093261719 wall_clock_time_millis_training 55.98807334899902 wall_clock_time_millis_training 47.971487045288086 wall_clock_time_millis_training 42.95206069946289 wall_clock_time_millis_training 42.97471046447754 wall_clock_time_millis_training 42.97471046447754 wall_clock_time_millis_training 44.95072364807129 wall_clock_time_millis_training 38.976430892944336 weighted_recall 0.135 [0.95,0,0.15,0.2,0,0.05,0,0,0,0] weighted_recall 0.125 [1,0,0,0.2,0,0,0,0,0.05,0] weighted_recall 0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.05,0.05,0.1,0,0,0,0.05,0] weighted_recall 0.145 [1,0,0.35,0.1,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0.15,0.05,0,0,0,0,0,0] weighted_recall 0.11 [0.95,0,0,0.1,0.05,0,0,0,0,0] weighted_recall 0.12 [1,0,0,0.15,0,0.05,0,0,0,0] weighted_recall 0.17 [1,0.05,0.1,0.5,0,0,0,0,0,0.05] weighted_recall 0.115 [1,0,0.1,0.05,0,0,0,0,0,0]