10578752 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) 8295034 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 "most_frequent" 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 0.23364904416188356 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 978 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 134 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 6 19038 random_state 2443 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.019233158853162298 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 22083771 description https://api.openml.org/data/download/22083771/description.xml -1 22083772 predictions https://api.openml.org/data/download/22083772/predictions.arff area_under_roc_curve 0.9996881674587158 [0.999978,0.999676,0.999938,0.999643,0.999748,0.99968,0.999899,0.999885,0.999441,0.998997] average_cost 0 f_measure 0.9793690373477639 [0.991855,0.976542,0.990081,0.978089,0.980634,0.983842,0.986571,0.981498,0.969314,0.955516] kappa 0.9770656031680932 kb_relative_information_score 0.9755604599145881 mean_absolute_error 0.006644094569059755 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9793594306049822 [0.98917,0.984238,0.985637,0.975524,0.980634,0.982079,0.987455,0.984099,0.969314,0.955516] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9793997525254327 [0.994555,0.968966,0.994565,0.980668,0.980634,0.985612,0.985689,0.97891,0.969314,0.955516] predictive_accuracy 0.9793594306049822 prior_entropy 3.3218327251668773 relative_absolute_error 0.03691217831939896 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.05641050154102081 root_relative_squared_error 0.18803638766262007 total_cost 0 unweighted_recall 0.9793666558739842 [0.98917,0.984238,0.985637,0.975524,0.980634,0.982079,0.987455,0.984099,0.969314,0.955516] area_under_roc_curve 0.9997958953252981 [1,0.999792,1,0.999932,0.999375,1,0.999788,0.999859,0.999749,0.999471] area_under_roc_curve 0.9998802985620501 [1,1,1,0.999589,0.999965,0.999965,1,0.999894,0.999821,0.999577] area_under_roc_curve 0.9997643789723057 [1,0.999965,1,0.999722,0.999965,1,1,1,0.999713,0.998271] area_under_roc_curve 0.9997078153258527 [1,0.999757,0.999788,0.998576,1,1,1,0.999965,0.999857,0.999153] area_under_roc_curve 0.9998487473661878 [0.999857,0.999861,1,1,1,0.999964,0.999894,1,0.99957,0.99934] area_under_roc_curve 0.9991316037944575 [0.999928,0.999826,1,0.999722,0.998958,0.997418,0.999647,0.999896,0.99792,0.99795] area_under_roc_curve 0.9998627929704577 [0.999965,0.999861,1,0.999792,1,0.999824,0.999928,0.999965,1,0.999294] area_under_roc_curve 0.9997078084448527 [1,0.99927,0.999964,0.999653,0.999896,0.999753,1,0.999548,0.999753,0.999259] area_under_roc_curve 0.9993913348262612 [1,0.999282,0.999821,0.999757,1,0.999224,1,0.999824,0.998377,0.997636] area_under_roc_curve 0.9998839269661145 [0.999965,0.999861,1,1,0.999894,0.999965,0.999753,1,0.999612,0.999788] 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 0.9750168226847596 [1,0.964912,0.990991,0.991453,0.955752,1,0.973451,0.973451,0.955752,0.944444] f_measure 0.985747200844913 [1,0.99115,1,0.973913,0.991304,0.982456,1,0.972477,0.972973,0.973451] f_measure 0.9875100207467798 [0.990826,0.991304,0.990991,0.973913,0.991304,1,1,0.991304,0.981818,0.963636] f_measure 0.9822029874520978 [1,0.974359,0.981818,0.964286,1,1,0.99115,0.99115,0.972973,0.946429] f_measure 0.9785757128162142 [0.981481,0.974359,1,0.991304,0.982759,0.981818,0.972477,0.991304,0.954955,0.954955] f_measure 0.9680851515929424 [0.990826,0.974359,0.990991,0.982143,0.947368,0.952381,0.973451,0.982456,0.954955,0.932203] f_measure 0.9839857651245552 [0.990991,0.973451,0.990991,0.982456,1,0.973451,0.990991,0.982456,0.990991,0.964286] f_measure 0.9733310405880372 [0.99115,0.982143,0.981818,0.954955,0.972973,0.973451,0.990991,0.957265,0.972973,0.956522] f_measure 0.9769559350786322 [0.99115,0.982759,0.972477,0.973913,0.990991,0.981818,1,0.973451,0.963636,0.93913] f_measure 0.9822298394481649 [0.982143,0.957265,1,0.991304,0.973451,0.99115,0.972973,1,0.972477,0.981818] kappa 0.9723205302300055 kappa 0.9841832157745687 kappa 0.9861600216711405 kappa 0.9802290197182107 kappa 0.976274155927767 kappa 0.9644106078623145 kappa 0.9822062429421263 kappa 0.9703440512207134 kappa 0.9742974543714732 kappa 0.9802289501642896 kb_relative_information_score 0.9771430417950016 kb_relative_information_score 0.9814697894224638 kb_relative_information_score 0.9810154659347781 kb_relative_information_score 0.9775098803842268 kb_relative_information_score 0.9767364364775372 kb_relative_information_score 0.9580254721919349 kb_relative_information_score 0.9790101173006474 kb_relative_information_score 0.9712837425396252 kb_relative_information_score 0.9727646155319838 kb_relative_information_score 0.9806458809393813 mean_absolute_error 0.0057723820372235475 mean_absolute_error 0.005482818375014947 mean_absolute_error 0.005969923847846652 mean_absolute_error 0.006686955508011911 mean_absolute_error 0.006418585336323033 mean_absolute_error 0.01104320413196624 mean_absolute_error 0.006145737519694418 mean_absolute_error 0.007253311524569541 mean_absolute_error 0.006797232316605085 mean_absolute_error 0.004870795093342195 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 0.9754117149114334 [1,0.964912,1,0.983051,0.964286,1,0.964912,0.964912,0.931034,0.980769] precision 0.9860132829927316 [1,1,1,0.982456,0.982759,0.965517,1,1,0.964286,0.964912] precision 0.9876319748389941 [1,0.982759,1,0.965517,0.982759,1,1,0.982759,0.981818,0.981481] precision 0.9825033710124552 [1,0.95,1,0.981818,1,1,0.982456,1,0.964286,0.946429] precision 0.9790930520316834 [1,0.95,1,0.982759,0.966102,0.981818,1,0.982759,0.946429,0.981481] precision 0.9690962664961218 [1,0.95,1,1,0.947368,1,0.964912,0.982456,0.946429,0.901639] precision 0.9840799730643335 [1,0.982143,0.982143,0.982456,1,0.964912,0.982143,0.982456,1,0.964286] precision 0.9740216035205972 [0.982456,1,0.981818,0.981481,1,0.964912,0.982143,0.933333,0.981818,0.932203] precision 0.9773768613347833 [0.982456,0.982759,0.981481,0.965517,1,1,1,0.964912,0.981481,0.915254] precision 0.9826542546976439 [0.982143,0.933333,1,0.982759,0.964912,0.982456,0.981818,1,1,1] predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9857651245551601 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9786476868327402 predictive_accuracy 0.9679715302491103 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9768683274021351 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 0.0320693634412829 relative_absolute_error 0.03046064761775036 relative_absolute_error 0.03316676771638529 relative_absolute_error 0.03715033988985167 relative_absolute_error 0.03565942102090391 relative_absolute_error 0.06135218976260583 relative_absolute_error 0.034143441841463666 relative_absolute_error 0.04029671286864074 relative_absolute_error 0.03776283937307219 relative_absolute_error 0.027060153290432716 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 0.058680656336650344 root_mean_squared_error 0.04775108114598012 root_mean_squared_error 0.04633451199518518 root_mean_squared_error 0.05217367256533184 root_mean_squared_error 0.05332629686282944 root_mean_squared_error 0.07404719665425549 root_mean_squared_error 0.049038012290332625 root_mean_squared_error 0.06296528637599091 root_mean_squared_error 0.062330206801794054 root_mean_squared_error 0.051456706699810895 root_relative_squared_error 0.1956042579071447 root_relative_squared_error 0.15917195503468798 root_relative_squared_error 0.15444968246042898 root_relative_squared_error 0.17391371600821565 root_relative_squared_error 0.17775607925847348 root_relative_squared_error 0.24682642770412 root_relative_squared_error 0.16346102467578266 root_relative_squared_error 0.20988555101065168 root_relative_squared_error 0.20776824154684448 root_relative_squared_error 0.17152224345970285 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 0.9751241740715425 [1,0.964912,0.982143,1,0.947368,1,0.982143,0.982143,0.981818,0.910714] unweighted_recall 0.9858362992119799 [1,0.982456,1,0.965517,1,1,1,0.946429,0.981818,0.982143] unweighted_recall 0.987466393255867 [0.981818,1,0.982143,0.982456,1,1,1,1,0.981818,0.946429] unweighted_recall 0.9822357028935975 [1,1,0.964286,0.947368,1,1,1,0.982456,0.981818,0.946429] unweighted_recall 0.9785344041922988 [0.963636,1,1,1,1,0.981818,0.946429,1,0.963636,0.929825] unweighted_recall 0.9678480291638186 [0.981818,1,0.982143,0.964912,0.947368,0.909091,0.982143,0.982456,0.963636,0.964912] unweighted_recall 0.9840538847117793 [0.982143,0.964912,1,0.982456,1,0.982143,1,0.982456,0.982143,0.964286] unweighted_recall 0.9734951013898382 [1,0.964912,0.981818,0.929825,0.947368,0.982143,1,0.982456,0.964286,0.982143] unweighted_recall 0.976813683896261 [1,0.982759,0.963636,0.982456,0.982143,0.964286,1,0.982143,0.946429,0.964286] unweighted_recall 0.982174185463659 [0.982143,0.982456,1,1,0.982143,1,0.964286,1,0.946429,0.964286] usercpu_time_millis 10785.197134000555 usercpu_time_millis 8483.591703999991 usercpu_time_millis 7430.641793000177 usercpu_time_millis 8186.00690400126 usercpu_time_millis 7220.2861919995485 usercpu_time_millis 6378.175478999765 usercpu_time_millis 7906.53669600033 usercpu_time_millis 8810.694509000314 usercpu_time_millis 8934.460710999701 usercpu_time_millis 9786.733120998178 usercpu_time_millis_testing 6.191200000102981 usercpu_time_millis_testing 5.377900000894442 usercpu_time_millis_testing 5.009399999835296 usercpu_time_millis_testing 5.43400000060501 usercpu_time_millis_testing 5.386700000599376 usercpu_time_millis_testing 5.585900000369293 usercpu_time_millis_testing 5.316200000379467 usercpu_time_millis_testing 5.491300000358024 usercpu_time_millis_testing 5.445500000860193 usercpu_time_millis_testing 6.043900999429752 usercpu_time_millis_training 10779.005934000452 usercpu_time_millis_training 8478.213803999097 usercpu_time_millis_training 7425.632393000342 usercpu_time_millis_training 8180.572904000655 usercpu_time_millis_training 7214.899491998949 usercpu_time_millis_training 6372.589578999396 usercpu_time_millis_training 7901.220495999951 usercpu_time_millis_training 8805.203208999956 usercpu_time_millis_training 8929.015210998841 usercpu_time_millis_training 9780.689219998749 wall_clock_time_millis 10834.322452545166 wall_clock_time_millis 8485.992908477783 wall_clock_time_millis 7432.092666625977 wall_clock_time_millis 8189.515590667725 wall_clock_time_millis 7228.601694107056 wall_clock_time_millis 6387.298822402954 wall_clock_time_millis 7928.473234176636 wall_clock_time_millis 8814.197778701782 wall_clock_time_millis 8942.626237869263 wall_clock_time_millis 9796.382427215576 wall_clock_time_millis_testing 6.193876266479492 wall_clock_time_millis_testing 5.383014678955078 wall_clock_time_millis_testing 5.017757415771484 wall_clock_time_millis_testing 5.436897277832031 wall_clock_time_millis_testing 5.395650863647461 wall_clock_time_millis_testing 5.589962005615234 wall_clock_time_millis_testing 5.318164825439453 wall_clock_time_millis_testing 5.49769401550293 wall_clock_time_millis_testing 5.859375 wall_clock_time_millis_testing 6.04701042175293 wall_clock_time_millis_training 10828.128576278687 wall_clock_time_millis_training 8480.609893798828 wall_clock_time_millis_training 7427.074909210205 wall_clock_time_millis_training 8184.078693389893 wall_clock_time_millis_training 7223.206043243408 wall_clock_time_millis_training 6381.708860397339 wall_clock_time_millis_training 7923.155069351196 wall_clock_time_millis_training 8808.70008468628 wall_clock_time_millis_training 8936.766862869263 wall_clock_time_millis_training 9790.335416793823 weighted_recall 0.9750889679715302 [1,0.964912,0.982143,1,0.947368,1,0.982143,0.982143,0.981818,0.910714] weighted_recall 0.9857651245551602 [1,0.982456,1,0.965517,1,1,1,0.946429,0.981818,0.982143] weighted_recall 0.9875444839857651 [0.981818,1,0.982143,0.982456,1,1,1,1,0.981818,0.946429] weighted_recall 0.9822064056939501 [1,1,0.964286,0.947368,1,1,1,0.982456,0.981818,0.946429] weighted_recall 0.9786476868327402 [0.963636,1,1,1,1,0.981818,0.946429,1,0.963636,0.929825] weighted_recall 0.9679715302491103 [0.981818,1,0.982143,0.964912,0.947368,0.909091,0.982143,0.982456,0.963636,0.964912] weighted_recall 0.9839857651245552 [0.982143,0.964912,1,0.982456,1,0.982143,1,0.982456,0.982143,0.964286] weighted_recall 0.9733096085409253 [1,0.964912,0.981818,0.929825,0.947368,0.982143,1,0.982456,0.964286,0.982143] weighted_recall 0.9768683274021353 [1,0.982759,0.963636,0.982456,0.982143,0.964286,1,0.982143,0.946429,0.964286] weighted_recall 0.9822064056939501 [0.982143,0.982456,1,1,0.982143,1,0.964286,1,0.946429,0.964286]