10578761 28997 Marc Boel 28 Supervised Classification 19037 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(1) 8295043 Python_3.8.10. Sklearn_0.24.2. NumPy_1.17.4. SciPy_1.3.3. add_indicator false 18819 copy true 18819 fill_value null 18819 missing_values NaN 18819 strategy "mean" 18819 verbose 0 18819 n_jobs null 18996 remainder "drop" 18996 sparse_threshold 0.3 18996 transformer_weights null 18996 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}] 18996 verbose false 18996 categories "auto" 18997 drop null 18997 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 18997 handle_unknown "ignore" 18997 sparse true 18997 memory null 19037 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 19037 verbose false 19037 ccp_alpha 0.0 19038 criterion "friedman_mse" 19038 init null 19038 learning_rate 0.49398513943468425 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 2043 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 196 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 8 19038 random_state 51751 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.06379074643649442 19038 verbose 0 19038 warm_start false 19038 openml-python Sklearn_0.24.2. 28 optdigits https://www.openml.org/data/download/28/dataset_28_optdigits.arff -1 22083789 description https://api.openml.org/data/download/22083789/description.xml -1 22083790 predictions https://api.openml.org/data/download/22083790/predictions.arff area_under_roc_curve 0.9995455713985041 [0.99996,0.999638,0.999846,0.999557,0.999738,0.998867,0.999772,0.999907,0.999485,0.998684] average_cost 0 f_measure 0.9818636863543444 [0.992767,0.981691,0.991039,0.979592,0.98326,0.981267,0.990135,0.98326,0.979223,0.956676] kappa 0.9798337157518542 kb_relative_information_score 0.9808978608961221 mean_absolute_error 0.004617598831013391 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9818505338078292 [0.990975,0.985989,0.992819,0.965035,0.982394,0.985663,0.989247,0.985866,0.978339,0.962633] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.981940342505429 [0.994565,0.977431,0.989267,0.994595,0.984127,0.976909,0.991023,0.980668,0.980108,0.950791] predictive_accuracy 0.9818505338078292 prior_entropy 3.3218327251668773 relative_absolute_error 0.025653703403251713 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.05423977397297207 root_relative_squared_error 0.18080057590160017 total_cost 0 unweighted_recall 0.9818961144831994 [0.990975,0.985989,0.992819,0.965035,0.982394,0.985663,0.989247,0.985866,0.978339,0.962633] area_under_roc_curve 0.9995141627802304 [1,0.999896,0.999859,0.999932,0.997151,1,0.999682,0.999824,0.999677,0.999153] area_under_roc_curve 0.9998168408663505 [1,1,1,0.999282,0.999896,0.999929,1,1,0.999928,0.999153] area_under_roc_curve 0.999894427784106 [1,1,1,0.999757,0.999861,1,1,1,1,0.999329] area_under_roc_curve 0.9997958537374657 [1,0.999861,0.999929,0.999166,1,1,1,0.999965,0.999928,0.999118] area_under_roc_curve 0.999905032723576 [0.999892,1,1,1,1,0.999857,1,1,0.999821,0.999479] area_under_roc_curve 0.9993777542354368 [0.999964,0.999896,1,0.99934,0.999792,0.997812,0.999682,0.999931,0.998745,0.998576] area_under_roc_curve 0.9998170503763182 [0.999894,0.999792,1,0.999861,1,1,0.999964,0.999861,0.999929,0.998871] area_under_roc_curve 0.999633877951076 [1,0.998923,0.999964,0.999583,0.999896,0.999435,1,0.999548,0.999753,0.999259] area_under_roc_curve 0.9989728118718038 [1,0.998632,0.998817,0.999826,1,0.997141,1,0.999859,0.998941,0.996506] area_under_roc_curve 0.9998733704408659 [0.999965,0.999826,1,1,0.999894,0.999859,0.999647,1,0.999753,0.999788] 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 0.9750995883248879 [0.990826,0.974359,0.973451,0.982456,0.964286,1,0.964912,0.973451,0.972477,0.954955] f_measure 0.9840580681153328 [1,0.99115,1,0.964286,0.982456,0.982456,1,0.990991,0.981818,0.948276] f_measure 0.9910981799551456 [1,1,1,0.982456,0.982456,1,1,0.974359,1,0.972477] f_measure 0.9838870262933754 [1,0.973913,0.981818,0.982143,0.991304,0.99115,0.99115,0.991304,0.990991,0.945455] f_measure 0.9911032025753629 [0.990826,0.991304,1,1,1,0.972973,0.990991,1,0.990991,0.973451] f_measure 0.9770033392189871 [0.990826,0.982759,1,0.982143,0.973913,0.953271,0.990991,0.99115,0.963636,0.941176] f_measure 0.9840625439192126 [0.990991,0.982143,0.990991,0.99115,0.991304,0.982456,0.990826,0.982456,0.990991,0.947368] f_measure 0.9713725181012854 [0.99115,0.964286,0.990991,0.944444,0.973451,0.955752,1,0.956522,0.973913,0.964912] f_measure 0.9786922683112532 [0.99115,0.982759,0.981818,0.973913,0.990991,0.990991,1,0.972973,0.954955,0.947368] f_measure 0.9821845088388147 [0.982143,0.974359,0.99115,0.99115,0.982143,0.982456,0.972973,1,0.972477,0.972973] kappa 0.9723204328538309 kappa 0.9822064933283144 kappa 0.990114370749795 kappa 0.9822060551478607 kappa 0.9901144403049396 kappa 0.9742966405505149 kappa 0.9822061803444783 kappa 0.9683673218111397 kappa 0.976274656731855 kappa 0.9802290892716424 kb_relative_information_score 0.9764897266836651 kb_relative_information_score 0.9832300555522261 kb_relative_information_score 0.9914335490945005 kb_relative_information_score 0.9836579303540308 kb_relative_information_score 0.9874897757202001 kb_relative_information_score 0.975296464823109 kb_relative_information_score 0.9794361631371544 kb_relative_information_score 0.9697988658755545 kb_relative_information_score 0.9801858026637145 kb_relative_information_score 0.9819603594874943 mean_absolute_error 0.005965763182803916 mean_absolute_error 0.0041414725895465 mean_absolute_error 0.0020977797606620188 mean_absolute_error 0.0036965554494070604 mean_absolute_error 0.003027003528139865 mean_absolute_error 0.005581878936731775 mean_absolute_error 0.005339833246495905 mean_absolute_error 0.007296397136476653 mean_absolute_error 0.004932094469284487 mean_absolute_error 0.004097210010585783 mean_prior_absolute_error 0.17999677629374952 mean_prior_absolute_error 0.17999677629374952 mean_prior_absolute_error 0.17999715555330845 mean_prior_absolute_error 0.17999715555330845 mean_prior_absolute_error 0.1799969027136025 mean_prior_absolute_error 0.1799969027136025 mean_prior_absolute_error 0.17999759802279386 mean_prior_absolute_error 0.17999759802279386 mean_prior_absolute_error 0.1799979140724263 mean_prior_absolute_error 0.17999879901139712 number_of_instances 562 [55,57,56,58,57,56,56,56,55,56] number_of_instances 562 [55,57,56,58,57,56,56,56,55,56] number_of_instances 562 [55,57,56,57,57,56,56,57,55,56] number_of_instances 562 [55,57,56,57,57,56,56,57,55,56] number_of_instances 562 [55,57,56,57,57,55,56,57,55,57] number_of_instances 562 [55,57,56,57,57,55,56,57,55,57] number_of_instances 562 [56,57,55,57,57,56,55,57,56,56] number_of_instances 562 [56,57,55,57,57,56,55,57,56,56] number_of_instances 562 [56,58,55,57,56,56,56,56,56,56] number_of_instances 562 [56,57,56,57,56,56,56,56,56,56] precision 0.9755024518206633 [1,0.95,0.964912,1,0.981818,1,0.948276,0.964912,0.981481,0.963636] precision 0.9847015993782469 [1,1,1,1,0.982456,0.965517,1,1,0.981818,0.916667] precision 0.9913701067615658 [1,1,1,0.982456,0.982456,1,1,0.95,1,1] precision 0.9840708831055561 [1,0.965517,1,1,0.982759,0.982456,0.982456,0.982759,0.982143,0.962963] precision 0.9911974300089407 [1,0.982759,1,1,1,0.964286,1,1,0.982143,0.982143] precision 0.9778086441794301 [1,0.966102,1,1,0.965517,0.980769,1,1,0.963636,0.903226] precision 0.9844163613414442 [1,1,0.982143,1,0.982759,0.965517,1,0.982456,1,0.931034] precision 0.9721379476670948 [0.982456,0.981818,0.982143,1,0.982143,0.947368,1,0.948276,0.949153,0.948276] precision 0.9788886338046389 [0.982456,0.982759,0.981818,0.965517,1,1,1,0.981818,0.963636,0.931034] precision 0.9825625369048521 [0.982143,0.95,0.982456,1,0.982143,0.965517,0.981818,1,1,0.981818] predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9911032028469751 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9911032028469751 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9786476868327402 predictive_accuracy 0.9822064056939501 prior_entropy 3.3217909017967746 prior_entropy 3.3217909017967746 prior_entropy 3.321817923867619 prior_entropy 3.321817923867619 prior_entropy 3.3217996202390836 prior_entropy 3.3217996202390836 prior_entropy 3.3218501976437715 prior_entropy 3.3218501976437715 prior_entropy 3.321873176216062 prior_entropy 3.3219367883600994 relative_absolute_error 0.03314372238016065 relative_absolute_error 0.0230085931249554 relative_absolute_error 0.01165451617395551 relative_absolute_error 0.020536743694887324 relative_absolute_error 0.01681697563960978 relative_absolute_error 0.03101097214774434 relative_absolute_error 0.02966613613265939 relative_absolute_error 0.04053608057343454 relative_absolute_error 0.027400842363650642 relative_absolute_error 0.022762429711135776 root_mean_prior_squared_error 0.2999968250410308 root_mean_prior_squared_error 0.2999968250410308 root_mean_prior_squared_error 0.2999974571463194 root_mean_prior_squared_error 0.2999974571463194 root_mean_prior_squared_error 0.2999970357429417 root_mean_prior_squared_error 0.2999970357429417 root_mean_prior_squared_error 0.2999981946008062 root_mean_prior_squared_error 0.2999981946008062 root_mean_prior_squared_error 0.2999987213529011 root_mean_prior_squared_error 0.3000001962538465 root_mean_squared_error 0.05926101301485864 root_mean_squared_error 0.05132992531480173 root_mean_squared_error 0.0375853595006103 root_mean_squared_error 0.05205285169245102 root_mean_squared_error 0.04226792859572453 root_mean_squared_error 0.06452025074477667 root_mean_squared_error 0.051153596630925974 root_mean_squared_error 0.06715592059247726 root_mean_squared_error 0.05642881787524177 root_mean_squared_error 0.05376321365275988 root_relative_squared_error 0.19753880064148505 root_relative_squared_error 0.17110156185080058 root_relative_squared_error 0.12528559361181046 root_relative_squared_error 0.17351097635158616 root_relative_squared_error 0.14089448747734504 root_relative_squared_error 0.21506962755479397 root_relative_squared_error 0.17051301491661883 root_relative_squared_error 0.22385441579686358 root_relative_squared_error 0.1880968612824925 root_relative_squared_error 0.17921059493997096 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 0.9751197350743629 [0.981818,1,0.982143,0.965517,0.947368,1,0.982143,0.982143,0.963636,0.946429] unweighted_recall 0.984205065956427 [1,0.982456,1,0.931034,0.982456,1,1,0.982143,0.981818,0.982143] unweighted_recall 0.9911340852130325 [1,1,1,0.982456,0.982456,1,1,1,1,0.946429] unweighted_recall 0.9840225563909775 [1,0.982456,0.964286,0.964912,1,1,1,1,1,0.928571] unweighted_recall 0.9910691501480976 [0.981818,1,1,1,1,0.981818,0.982143,1,1,0.964912] unweighted_recall 0.9767150831624514 [0.981818,1,1,0.964912,0.982456,0.927273,0.982143,0.982456,0.963636,0.982456] unweighted_recall 0.9840214171793118 [0.982143,0.964912,1,0.982456,1,1,0.981818,0.982456,0.982143,0.964286] unweighted_recall 0.9718358395989976 [1,0.947368,1,0.894737,0.964912,0.964286,1,0.964912,1,0.982143] unweighted_recall 0.9786318657144427 [1,0.982759,0.981818,0.982456,0.982143,0.982143,1,0.964286,0.946429,0.964286] unweighted_recall 0.982174185463659 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.946429,0.964286] usercpu_time_millis 4586.897351999141 usercpu_time_millis 7715.527594000378 usercpu_time_millis 11241.617841000334 usercpu_time_millis 9771.324120998543 usercpu_time_millis 7489.614092999545 usercpu_time_millis 11210.73884100042 usercpu_time_millis 4275.331353999718 usercpu_time_millis 5343.5958639984165 usercpu_time_millis 6833.133182000893 usercpu_time_millis 8716.018107998025 usercpu_time_millis_testing 4.263900998921599 usercpu_time_millis_testing 6.45280000026105 usercpu_time_millis_testing 6.974699999773293 usercpu_time_millis_testing 6.234799999219831 usercpu_time_millis_testing 6.308899999567075 usercpu_time_millis_testing 6.88350000018545 usercpu_time_millis_testing 5.2015000001119915 usercpu_time_millis_testing 5.74869999945804 usercpu_time_millis_testing 5.258699000478373 usercpu_time_millis_testing 5.771999998614774 usercpu_time_millis_training 4582.63345100022 usercpu_time_millis_training 7709.0747940001165 usercpu_time_millis_training 11234.64314100056 usercpu_time_millis_training 9765.089320999323 usercpu_time_millis_training 7483.305192999978 usercpu_time_millis_training 11203.855341000235 usercpu_time_millis_training 4270.129853999606 usercpu_time_millis_training 5337.847163998958 usercpu_time_millis_training 6827.874483000414 usercpu_time_millis_training 8710.24610799941 wall_clock_time_millis 4593.696355819702 wall_clock_time_millis 7717.852830886841 wall_clock_time_millis 11248.443603515625 wall_clock_time_millis 9772.43685722351 wall_clock_time_millis 7492.202997207642 wall_clock_time_millis 11216.73035621643 wall_clock_time_millis 4280.600070953369 wall_clock_time_millis 5368.893146514893 wall_clock_time_millis 6841.678619384766 wall_clock_time_millis 8730.984926223755 wall_clock_time_millis_testing 4.266023635864258 wall_clock_time_millis_testing 6.4563751220703125 wall_clock_time_millis_testing 6.97779655456543 wall_clock_time_millis_testing 6.238222122192383 wall_clock_time_millis_testing 6.322622299194336 wall_clock_time_millis_testing 6.885051727294922 wall_clock_time_millis_testing 5.207538604736328 wall_clock_time_millis_testing 5.752801895141602 wall_clock_time_millis_testing 5.265712738037109 wall_clock_time_millis_testing 5.775213241577148 wall_clock_time_millis_training 4589.430332183838 wall_clock_time_millis_training 7711.3964557647705 wall_clock_time_millis_training 11241.46580696106 wall_clock_time_millis_training 9766.198635101318 wall_clock_time_millis_training 7485.880374908447 wall_clock_time_millis_training 11209.845304489136 wall_clock_time_millis_training 4275.392532348633 wall_clock_time_millis_training 5363.140344619751 wall_clock_time_millis_training 6836.4129066467285 wall_clock_time_millis_training 8725.209712982178 weighted_recall 0.9750889679715302 [0.981818,1,0.982143,0.965517,0.947368,1,0.982143,0.982143,0.963636,0.946429] weighted_recall 0.9839857651245552 [1,0.982456,1,0.931034,0.982456,1,1,0.982143,0.981818,0.982143] weighted_recall 0.9911032028469751 [1,1,1,0.982456,0.982456,1,1,1,1,0.946429] weighted_recall 0.9839857651245552 [1,0.982456,0.964286,0.964912,1,1,1,1,1,0.928571] weighted_recall 0.9911032028469751 [0.981818,1,1,1,1,0.981818,0.982143,1,1,0.964912] weighted_recall 0.9768683274021353 [0.981818,1,1,0.964912,0.982456,0.927273,0.982143,0.982456,0.963636,0.982456] weighted_recall 0.9839857651245552 [0.982143,0.964912,1,0.982456,1,1,0.981818,0.982456,0.982143,0.964286] weighted_recall 0.9715302491103203 [1,0.947368,1,0.894737,0.964912,0.964286,1,0.964912,1,0.982143] weighted_recall 0.9786476868327402 [1,0.982759,0.981818,0.982456,0.982143,0.982143,1,0.964286,0.946429,0.964286] weighted_recall 0.9822064056939501 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.946429,0.964286]