10588251 32117 VAIBHAV JAISWAL 18 Supervised Classification 19174 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1) 8304109 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 19174 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"}}] 19174 verbose false 19174 categorical_features null 19175 early_stopping "auto" 19175 l2_regularization 0.0 19175 learning_rate 0.1 19175 loss "auto" 19175 max_bins 255 19175 max_depth null 19175 max_iter 100 19175 max_leaf_nodes 31 19175 min_samples_leaf 20 19175 monotonic_cst null 19175 n_iter_no_change 10 19175 random_state 0 19175 scoring "loss" 19175 tol 1e-07 19175 validation_fraction 0.1 19175 verbose 0 19175 warm_start false 19175 openml-python Sklearn_1.0.2. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22104069 description https://api.openml.org/data/download/22104069/description.xml -1 22104070 predictions https://api.openml.org/data/download/22104070/predictions.arff area_under_roc_curve 0.5353144444444444 [0.99915,0.307214,0.707519,0.690971,0.587286,0.386454,0.535971,0.343853,0.161283,0.633443] average_cost 0 f_measure 0.12782146671658295 [0.98995,0.009877,0.096692,0.151515,0.020305,0,0,0,0.009877,0] kappa 0.029999999999999995 kb_relative_information_score 0.09179512135030095 mean_absolute_error 0.1744223152200107 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.127 [0.985,0.01,0.095,0.15,0.02,0,0,0,0.01,0] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.12865870671171953 [0.994949,0.009756,0.098446,0.153061,0.020619,0,0,0,0.009756,0] predictive_accuracy 0.127 prior_entropy 3.3219280948872383 relative_absolute_error 0.9690128623333629 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.40142129792555986 root_relative_squared_error 1.338070993085179 total_cost 0 unweighted_recall 0.127 [0.985,0.01,0.095,0.15,0.02,0,0,0,0.01,0] area_under_roc_curve 0.5305277777777778 [0.999167,0.329167,0.671944,0.761111,0.553889,0.329722,0.5875,0.368611,0.098889,0.605278] area_under_roc_curve 0.5336666666666667 [1,0.296944,0.759722,0.674722,0.625833,0.395833,0.517083,0.350278,0.101944,0.614306] area_under_roc_curve 0.5414166666666667 [0.997222,0.265833,0.632222,0.705556,0.596667,0.4775,0.523194,0.412222,0.142222,0.661528] area_under_roc_curve 0.5230833333333333 [1,0.314444,0.674167,0.715972,0.555556,0.414306,0.46375,0.290833,0.167222,0.634583] area_under_roc_curve 0.5403611111111111 [1,0.316389,0.701944,0.736667,0.633611,0.421389,0.533889,0.365,0.096111,0.598611] area_under_roc_curve 0.5278611111111111 [1,0.264444,0.755556,0.525556,0.622778,0.348611,0.567639,0.305,0.228056,0.660972] area_under_roc_curve 0.5155555555555555 [0.998611,0.280556,0.693056,0.633056,0.602778,0.291389,0.580139,0.337222,0.118611,0.620139] area_under_roc_curve 0.5437500000000001 [1,0.326667,0.706111,0.725278,0.585,0.404722,0.479306,0.3075,0.262778,0.640139] area_under_roc_curve 0.5369999999999999 [1,0.372778,0.704722,0.715833,0.554722,0.426389,0.492778,0.326389,0.16,0.616389] area_under_roc_curve 0.5481666666666666 [1,0.310278,0.746111,0.7075,0.545,0.333889,0.589861,0.357778,0.222778,0.668472] 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 0.14294871794871794 [0.974359,0,0.205128,0.25,0,0,0,0,0,0] f_measure 0.1178433889602054 [0.97561,0,0.105263,0.097561,0,0,0,0,0,0] f_measure 0.12637159588379102 [0.974359,0,0.045455,0.243902,0,0,0,0,0,0] f_measure 0.12612246392734197 [1,0,0.055556,0.108108,0.097561,0,0,0,0,0] f_measure 0.1346282372598162 [1,0,0.055556,0.238095,0.052632,0,0,0,0,0] f_measure 0.12907268170426067 [1,0,0.238095,0,0.052632,0,0,0,0,0] f_measure 0.10769230769230768 [0.974359,0,0,0.102564,0,0,0,0,0,0] f_measure 0.12640763031006932 [1,0.04878,0.045455,0.114286,0,0,0,0,0.055556,0] f_measure 0.1314227642276423 [1,0.05,0.097561,0.166667,0,0,0,0,0,0] f_measure 0.13146434960388448 [1,0,0.114286,0.153846,0,0,0,0,0.046512,0] kappa 0.04444444444444445 kappa 0.02222222222222221 kappa 0.02777777777777777 kappa 0.02777777777777777 kappa 0.03888888888888889 kappa 0.03333333333333333 kappa 0.005555555555555545 kappa 0.02777777777777777 kappa 0.03888888888888889 kappa 0.03333333333333333 kb_relative_information_score 0.10085470487601661 kb_relative_information_score 0.09133677492496128 kb_relative_information_score 0.08404705174750551 kb_relative_information_score 0.08772565959592324 kb_relative_information_score 0.1006985675526039 kb_relative_information_score 0.09315259102684069 kb_relative_information_score 0.06920858673578743 kb_relative_information_score 0.08779485238955305 kb_relative_information_score 0.1047070279482166 kb_relative_information_score 0.09842539670556763 mean_absolute_error 0.17281448647383407 mean_absolute_error 0.1747298451843104 mean_absolute_error 0.17591452710360894 mean_absolute_error 0.17480155609683531 mean_absolute_error 0.17284754948107497 mean_absolute_error 0.17422646501154396 mean_absolute_error 0.17819350569494755 mean_absolute_error 0.17547390606365845 mean_absolute_error 0.17183679620014178 mean_absolute_error 0.1733845148901528 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 0.14605263157894735 [1,0,0.210526,0.25,0,0,0,0,0,0] precision 0.11587301587301586 [0.952381,0,0.111111,0.095238,0,0,0,0,0,0] precision 0.12797619047619047 [1,0,0.041667,0.238095,0,0,0,0,0,0] precision 0.12753851540616246 [1,0,0.0625,0.117647,0.095238,0,0,0,0,0] precision 0.13453282828282828 [1,0,0.0625,0.227273,0.055556,0,0,0,0,0] precision 0.12828282828282828 [1,0,0.227273,0,0.055556,0,0,0,0,0] precision 0.11052631578947368 [1,0,0,0.105263,0,0,0,0,0,0] precision 0.12851190476190477 [1,0.047619,0.041667,0.133333,0,0,0,0,0.0625,0] precision 0.12880952380952382 [1,0.05,0.095238,0.142857,0,0,0,0,0,0] precision 0.13347063310450039 [1,0,0.133333,0.157895,0,0,0,0,0.043478,0] predictive_accuracy 0.14 predictive_accuracy 0.12 predictive_accuracy 0.125 predictive_accuracy 0.125 predictive_accuracy 0.135 predictive_accuracy 0.13 predictive_accuracy 0.105 predictive_accuracy 0.125 predictive_accuracy 0.135 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 0.9600804804101903 relative_absolute_error 0.9707213621350589 relative_absolute_error 0.9773029283533841 relative_absolute_error 0.9711197560935306 relative_absolute_error 0.9602641637837509 relative_absolute_error 0.9679248056196897 relative_absolute_error 0.9899639205274875 relative_absolute_error 0.9748550336869924 relative_absolute_error 0.9546488677785665 relative_absolute_error 0.9632473049452944 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 0.3999703539085684 root_mean_squared_error 0.4013732114243645 root_mean_squared_error 0.4042772091721088 root_mean_squared_error 0.4025365554729897 root_mean_squared_error 0.40061656218271097 root_mean_squared_error 0.399541974656886 root_mean_squared_error 0.40728419962962115 root_mean_squared_error 0.3994406604263493 root_mean_squared_error 0.3975671163273777 root_mean_squared_error 0.4015193808735094 root_relative_squared_error 1.3332345130285619 root_relative_squared_error 1.3379107047478822 root_relative_squared_error 1.3475906972403633 root_relative_squared_error 1.3417885182432996 root_relative_squared_error 1.3353885406090373 root_relative_squared_error 1.331806582189621 root_relative_squared_error 1.3576139987654046 root_relative_squared_error 1.3314688680878317 root_relative_squared_error 1.3252237210912596 root_relative_squared_error 1.3383979362450322 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 [0.95,0,0.2,0.25,0,0,0,0,0,0] unweighted_recall 0.12000000000000002 [1,0,0.1,0.1,0,0,0,0,0,0] unweighted_recall 0.125 [0.95,0,0.05,0.25,0,0,0,0,0,0] unweighted_recall 0.12500000000000003 [1,0,0.05,0.1,0.1,0,0,0,0,0] unweighted_recall 0.135 [1,0,0.05,0.25,0.05,0,0,0,0,0] unweighted_recall 0.13 [1,0,0.25,0,0.05,0,0,0,0,0] unweighted_recall 0.10500000000000001 [0.95,0,0,0.1,0,0,0,0,0,0] unweighted_recall 0.12500000000000003 [1,0.05,0.05,0.1,0,0,0,0,0.05,0] unweighted_recall 0.135 [1,0.05,0.1,0.2,0,0,0,0,0,0] unweighted_recall 0.13 [1,0,0.1,0.15,0,0,0,0,0.05,0] usercpu_time_millis 34718.75 usercpu_time_millis 34828.125 usercpu_time_millis 34828.125 usercpu_time_millis 35406.25 usercpu_time_millis 35781.25 usercpu_time_millis 35812.5 usercpu_time_millis 35328.125 usercpu_time_millis 34953.125 usercpu_time_millis 35218.75 usercpu_time_millis 35515.625 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 125 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_testing 187.5 usercpu_time_millis_training 34531.25 usercpu_time_millis_training 34640.625 usercpu_time_millis_training 34640.625 usercpu_time_millis_training 35218.75 usercpu_time_millis_training 35593.75 usercpu_time_millis_training 35625 usercpu_time_millis_training 35203.125 usercpu_time_millis_training 34765.625 usercpu_time_millis_training 35031.25 usercpu_time_millis_training 35328.125 wall_clock_time_millis 9112.754583358765 wall_clock_time_millis 9144.757509231567 wall_clock_time_millis 9300.668239593506 wall_clock_time_millis 9143.758296966553 wall_clock_time_millis 9172.741889953613 wall_clock_time_millis 9209.720134735107 wall_clock_time_millis 9197.728633880615 wall_clock_time_millis 9231.709241867065 wall_clock_time_millis 9158.750057220459 wall_clock_time_millis 9159.749984741211 wall_clock_time_millis_testing 48.970937728881836 wall_clock_time_millis_testing 50.971269607543945 wall_clock_time_millis_testing 51.97024345397949 wall_clock_time_millis_testing 48.97141456604004 wall_clock_time_millis_testing 49.97134208679199 wall_clock_time_millis_testing 51.969289779663086 wall_clock_time_millis_testing 69.95749473571777 wall_clock_time_millis_testing 49.97134208679199 wall_clock_time_millis_testing 49.971580505371094 wall_clock_time_millis_testing 49.971580505371094 wall_clock_time_millis_training 9063.783645629883 wall_clock_time_millis_training 9093.786239624023 wall_clock_time_millis_training 9248.697996139526 wall_clock_time_millis_training 9094.786882400513 wall_clock_time_millis_training 9122.770547866821 wall_clock_time_millis_training 9157.750844955444 wall_clock_time_millis_training 9127.771139144897 wall_clock_time_millis_training 9181.737899780273 wall_clock_time_millis_training 9108.778476715088 wall_clock_time_millis_training 9109.77840423584 weighted_recall 0.14 [0.95,0,0.2,0.25,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0.1,0.1,0,0,0,0,0,0] weighted_recall 0.125 [0.95,0,0.05,0.25,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.05,0.1,0.1,0,0,0,0,0] weighted_recall 0.135 [1,0,0.05,0.25,0.05,0,0,0,0,0] weighted_recall 0.13 [1,0,0.25,0,0.05,0,0,0,0,0] weighted_recall 0.105 [0.95,0,0,0.1,0,0,0,0,0,0] weighted_recall 0.125 [1,0.05,0.05,0.1,0,0,0,0,0.05,0] weighted_recall 0.135 [1,0.05,0.1,0.2,0,0,0,0,0,0] weighted_recall 0.13 [1,0,0.1,0.15,0,0,0,0,0.05,0]