10578756 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) 8295038 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 "median" 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 0.4135186749303344 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1984 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 172 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 7 19038 random_state 34908 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.09832313171649718 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 22083779 description https://api.openml.org/data/download/22083779/description.xml -1 22083780 predictions https://api.openml.org/data/download/22083780/predictions.arff area_under_roc_curve 0.9995966511156075 [0.999954,0.999644,0.999901,0.999725,0.999554,0.999606,0.99964,0.999878,0.999219,0.998844] average_cost 0 f_measure 0.9784911911658271 [0.99187,0.976542,0.990099,0.972735,0.98326,0.983784,0.986547,0.976211,0.972047,0.952212] kappa 0.9760770987102347 kb_relative_information_score 0.978815545559951 mean_absolute_error 0.005315596740978068 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9784697508896797 [0.990975,0.984238,0.987433,0.966783,0.982394,0.978495,0.985663,0.978799,0.972924,0.957295] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.978546779800128 [0.992767,0.968966,0.99278,0.978761,0.984127,0.98913,0.987433,0.973638,0.971171,0.947183] predictive_accuracy 0.9784697508896797 prior_entropy 3.3218327251668773 relative_absolute_error 0.029531526491316226 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.056338732864910784 root_relative_squared_error 0.18779715698332455 total_cost 0 unweighted_recall 0.9784999019957876 [0.990975,0.984238,0.987433,0.966783,0.982394,0.978495,0.985663,0.978799,0.972924,0.957295] area_under_roc_curve 0.9996373733339198 [1,0.999687,1,0.999932,0.998055,1,0.999753,0.999894,0.999713,0.999365] area_under_roc_curve 0.9999119542935526 [1,1,1,0.999624,1,0.999929,1,0.999929,0.999892,0.999753] area_under_roc_curve 0.9997749077538021 [1,0.999931,1,0.999826,0.999931,1,1,1,0.999857,0.9982] area_under_roc_curve 0.9996516900169526 [1,0.999653,0.999577,0.999062,1,1,1,0.999965,0.999534,0.99873] area_under_roc_curve 0.9998663716947618 [0.999928,0.999931,1,1,1,0.999713,1,1,0.999677,0.999409] area_under_roc_curve 0.9992404013039728 [0.999821,0.999896,0.999894,0.999409,0.999166,0.998566,0.998765,0.999826,0.998494,0.998541] area_under_roc_curve 0.9998944347200441 [0.999929,0.999792,1,0.999896,1,0.999788,0.999964,0.999931,1,0.999647] area_under_roc_curve 0.9993455649862456 [1,0.999062,0.999964,0.999687,0.999896,0.999647,0.999928,0.999444,0.998165,0.997671] area_under_roc_curve 0.9993703191264455 [1,0.99935,0.99957,0.999792,1,0.998765,1,0.999929,0.998906,0.997388] area_under_roc_curve 0.999824139152272 [0.999929,0.999896,1,0.999931,0.999965,0.999929,0.999859,1,0.999047,0.999682] 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 0.9731629772117011 [1,0.965517,0.990991,0.97479,0.955752,1,0.973451,0.972973,0.964286,0.934579] f_measure 0.9892919371474848 [1,1,1,0.973451,0.991304,0.982456,1,0.982143,0.981818,0.982143] f_measure 0.9822195878316559 [1,0.982456,0.990991,0.973451,0.973451,1,1,0.974359,0.981818,0.946429] f_measure 0.9733841810470472 [0.990826,0.964912,0.981818,0.955752,0.991304,1,0.99115,0.973451,0.945455,0.93913] f_measure 0.9857588245054935 [0.990826,0.974359,1,1,1,0.990826,0.972477,0.991304,0.973451,0.964286] f_measure 0.9698886044271656 [0.981818,0.982759,0.981818,0.973913,0.973913,0.952381,0.990991,0.973451,0.963636,0.92437] f_measure 0.9839698816544551 [0.990991,0.973451,0.990991,0.982456,0.991304,0.982143,0.981818,0.982456,1,0.964286] f_measure 0.9678977359976929 [0.99115,0.973451,0.982143,0.954128,0.973451,0.954955,0.982143,0.93913,0.972973,0.956522] f_measure 0.9751631151670039 [0.99115,0.982759,0.981818,0.955752,0.990991,0.981818,1,0.973451,0.954955,0.93913] f_measure 0.9840258150164007 [0.982143,0.966102,1,0.982456,0.990991,0.99115,0.972973,1,0.981818,0.972973] kappa 0.9703426949097088 kappa 0.9881374952947509 kappa 0.9802288806098791 kappa 0.9703434252464346 kappa 0.9841829931996722 kappa 0.9663874415544665 kappa 0.9822061177463897 kappa 0.9644133622266625 kappa 0.972320627605495 kappa 0.9822060551478607 kb_relative_information_score 0.9754280375812917 kb_relative_information_score 0.9873914505150718 kb_relative_information_score 0.9832127858847736 kb_relative_information_score 0.9754228507061099 kb_relative_information_score 0.9839838844937643 kb_relative_information_score 0.9686384143078268 kb_relative_information_score 0.9834177205301802 kb_relative_information_score 0.9690551620714156 kb_relative_information_score 0.9777490928814382 kb_relative_information_score 0.9838559587273101 mean_absolute_error 0.005552528263462872 mean_absolute_error 0.003409313172932004 mean_absolute_error 0.004702647123188971 mean_absolute_error 0.006701554605840424 mean_absolute_error 0.004230626021409289 mean_absolute_error 0.007312424780809065 mean_absolute_error 0.0037595844151594535 mean_absolute_error 0.00807195950128031 mean_absolute_error 0.005619198427058582 mean_absolute_error 0.0037961310986397018 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 0.9737324759011947 [1,0.949153,1,0.95082,0.964286,1,0.964912,0.981818,0.947368,0.980392] precision 0.9894772364707326 [1,1,1,1,0.982759,0.965517,1,0.982143,0.981818,0.982143] precision 0.9824097610574478 [1,0.982456,1,0.982143,0.982143,1,1,0.95,0.981818,0.946429] precision 0.9737285606735296 [1,0.964912,1,0.964286,0.982759,1,0.982456,0.982143,0.945455,0.915254] precision 0.986274110599181 [1,0.95,1,1,1,1,1,0.982759,0.948276,0.981818] precision 0.970966941483249 [0.981818,0.966102,1,0.965517,0.965517,1,1,0.982143,0.963636,0.887097] precision 0.9840164437354276 [1,0.982143,0.982143,0.982456,0.982759,0.982143,0.981818,0.982456,1,0.964286] precision 0.9685764952746125 [0.982456,0.982143,0.964912,1,0.982143,0.963636,0.964912,0.931034,0.981818,0.932203] precision 0.9755067454537457 [0.982456,0.982759,0.981818,0.964286,1,1,1,0.964912,0.963636,0.915254] precision 0.9844189952050759 [0.982143,0.934426,1,0.982456,1,0.982456,0.981818,1,1,0.981818] predictive_accuracy 0.9733096085409252 predictive_accuracy 0.98932384341637 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9857651245551601 predictive_accuracy 0.9697508896797153 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9679715302491103 predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9839857651245552 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 0.03084793171185081 relative_absolute_error 0.018940967961382286 relative_absolute_error 0.02612623021032253 relative_absolute_error 0.03723144727059686 relative_absolute_error 0.02350388233146846 relative_absolute_error 0.04062528116077666 relative_absolute_error 0.020886858805101174 relative_absolute_error 0.04484481787505922 relative_absolute_error 0.031218130810102433 relative_absolute_error 0.021089757928881177 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 0.06329998956767378 root_mean_squared_error 0.04255194438657118 root_mean_squared_error 0.04720013007795543 root_mean_squared_error 0.05799397970106617 root_mean_squared_error 0.047296658357234546 root_mean_squared_error 0.07152984613518433 root_mean_squared_error 0.04893590858521034 root_mean_squared_error 0.06593208442817437 root_mean_squared_error 0.05975949814112952 root_mean_squared_error 0.05162716622942935 root_relative_squared_error 0.21100219830331934 root_relative_squared_error 0.14184131575642947 root_relative_squared_error 0.15733510052698294 root_relative_squared_error 0.19331490424193976 root_relative_squared_error 0.1576570856445449 root_relative_squared_error 0.23843517639446304 root_relative_squared_error 0.16312067694382995 root_relative_squared_error 0.21977493736556372 root_relative_squared_error 0.1991991761552607 root_relative_squared_error 0.17209044152006087 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 0.9733071314650262 [1,0.982456,0.982143,1,0.947368,1,0.982143,0.964286,0.981818,0.892857] unweighted_recall 0.9894379758172862 [1,1,1,0.948276,1,1,1,0.982143,0.981818,0.982143] unweighted_recall 0.9822670312143996 [1,0.982456,0.982143,0.964912,0.964912,1,1,1,0.981818,0.946429] unweighted_recall 0.9733037138300296 [0.981818,0.964912,0.964286,0.947368,1,1,1,0.964912,0.945455,0.964286] unweighted_recall 0.9857433356117566 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.947368] unweighted_recall 0.969571086807929 [0.981818,1,0.964286,0.982456,0.982456,0.909091,0.982143,0.964912,0.963636,0.964912] unweighted_recall 0.9840214171793118 [0.982143,0.964912,1,0.982456,1,0.982143,0.981818,0.982456,1,0.964286] unweighted_recall 0.968233082706767 [1,0.964912,1,0.912281,0.964912,0.946429,1,0.947368,0.964286,0.982143] unweighted_recall 0.9751230937846183 [1,0.982759,0.981818,0.947368,0.982143,0.964286,1,0.982143,0.946429,0.964286] unweighted_recall 0.9839598997493733 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.964286,0.964286] usercpu_time_millis 8220.802103998722 usercpu_time_millis 8337.30650600046 usercpu_time_millis 5679.115669998282 usercpu_time_millis 5802.288273000158 usercpu_time_millis 5625.758772001063 usercpu_time_millis 8116.283099001521 usercpu_time_millis 8040.21740099779 usercpu_time_millis 4126.026950998494 usercpu_time_millis 6812.292583999806 usercpu_time_millis 9736.447425000733 usercpu_time_millis_testing 5.447699999422184 usercpu_time_millis_testing 5.759300000136136 usercpu_time_millis_testing 5.3633999996236525 usercpu_time_millis_testing 5.963800000245101 usercpu_time_millis_testing 4.912899999908404 usercpu_time_millis_testing 5.686000000423519 usercpu_time_millis_testing 6.701099999190774 usercpu_time_millis_testing 4.694200999438181 usercpu_time_millis_testing 5.37360000089393 usercpu_time_millis_testing 6.23980000091251 usercpu_time_millis_training 8215.3544039993 usercpu_time_millis_training 8331.547206000323 usercpu_time_millis_training 5673.752269998658 usercpu_time_millis_training 5796.324472999913 usercpu_time_millis_training 5620.845872001155 usercpu_time_millis_training 8110.597099001097 usercpu_time_millis_training 8033.516300998599 usercpu_time_millis_training 4121.3327499990555 usercpu_time_millis_training 6806.918983998912 usercpu_time_millis_training 9730.20762499982 wall_clock_time_millis 8226.499557495117 wall_clock_time_millis 8342.768669128418 wall_clock_time_millis 5683.728456497192 wall_clock_time_millis 5822.530031204224 wall_clock_time_millis 5645.063877105713 wall_clock_time_millis 8131.55460357666 wall_clock_time_millis 8044.487953186035 wall_clock_time_millis 4131.649732589722 wall_clock_time_millis 6815.8416748046875 wall_clock_time_millis 9739.264011383057 wall_clock_time_millis_testing 5.450248718261719 wall_clock_time_millis_testing 5.762815475463867 wall_clock_time_millis_testing 5.369424819946289 wall_clock_time_millis_testing 5.967617034912109 wall_clock_time_millis_testing 5.03087043762207 wall_clock_time_millis_testing 5.692720413208008 wall_clock_time_millis_testing 6.704807281494141 wall_clock_time_millis_testing 4.697084426879883 wall_clock_time_millis_testing 5.377769470214844 wall_clock_time_millis_testing 6.244421005249023 wall_clock_time_millis_training 8221.049308776855 wall_clock_time_millis_training 8337.005853652954 wall_clock_time_millis_training 5678.359031677246 wall_clock_time_millis_training 5816.5624141693115 wall_clock_time_millis_training 5640.033006668091 wall_clock_time_millis_training 8125.861883163452 wall_clock_time_millis_training 8037.783145904541 wall_clock_time_millis_training 4126.952648162842 wall_clock_time_millis_training 6810.463905334473 wall_clock_time_millis_training 9733.019590377808 weighted_recall 0.9733096085409253 [1,0.982456,0.982143,1,0.947368,1,0.982143,0.964286,0.981818,0.892857] weighted_recall 0.9893238434163701 [1,1,1,0.948276,1,1,1,0.982143,0.981818,0.982143] weighted_recall 0.9822064056939501 [1,0.982456,0.982143,0.964912,0.964912,1,1,1,0.981818,0.946429] weighted_recall 0.9733096085409253 [0.981818,0.964912,0.964286,0.947368,1,1,1,0.964912,0.945455,0.964286] weighted_recall 0.9857651245551602 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.947368] weighted_recall 0.9697508896797153 [0.981818,1,0.964286,0.982456,0.982456,0.909091,0.982143,0.964912,0.963636,0.964912] weighted_recall 0.9839857651245552 [0.982143,0.964912,1,0.982456,1,0.982143,0.981818,0.982456,1,0.964286] weighted_recall 0.9679715302491103 [1,0.964912,1,0.912281,0.964912,0.946429,1,0.947368,0.964286,0.982143] weighted_recall 0.9750889679715302 [1,0.982759,0.981818,0.947368,0.982143,0.964286,1,0.982143,0.946429,0.964286] weighted_recall 0.9839857651245552 [0.982143,1,1,0.982456,0.982143,1,0.964286,1,0.964286,0.964286]