10578828 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) 8295110 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 0.1398256092300441 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 406 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 95 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 44857 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.30514739720467254 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 22083923 description https://api.openml.org/data/download/22083923/description.xml -1 22083925 predictions https://api.openml.org/data/download/22083925/predictions.arff area_under_roc_curve 0.9995397058640785 [0.999936,0.999663,0.999918,0.999568,0.999792,0.999195,0.999644,0.999828,0.999347,0.998503] average_cost 0 f_measure 0.9754865929371763 [0.990958,0.969749,0.990991,0.974494,0.981498,0.978339,0.984698,0.976211,0.964896,0.943363] kappa 0.9727159579456506 kb_relative_information_score 0.9737280276590811 mean_absolute_error 0.006749329082896463 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9754448398576513 [0.98917,0.982487,0.987433,0.968531,0.980634,0.971326,0.980287,0.978799,0.967509,0.948399] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.975594504708869 [0.992754,0.957338,0.994575,0.980531,0.982363,0.985455,0.98915,0.973638,0.962298,0.93838] predictive_accuracy 0.9754448398576513 prior_entropy 3.3218327251668773 relative_absolute_error 0.03749682308923485 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.06001867549306802 root_relative_squared_error 0.20006372259967864 total_cost 0 unweighted_recall 0.9754573578213824 [0.98917,0.982487,0.987433,0.968531,0.980634,0.971326,0.980287,0.978799,0.967509,0.948399] area_under_roc_curve 0.9995532689726595 [1,0.999583,0.999965,0.999932,0.999201,1,0.999012,0.999824,0.999283,0.99873] area_under_roc_curve 0.9998310528786869 [1,1,1,0.999384,0.999931,0.999859,1,1,0.999426,0.999718] area_under_roc_curve 0.9997467476528554 [1,1,0.999929,0.999444,1,1,1,1,0.999749,0.998341] area_under_roc_curve 0.9994826465645831 [1,0.999409,0.999718,0.998506,1,0.999965,1,0.999792,0.999821,0.997636] area_under_roc_curve 0.9997047504378178 [0.999785,0.999826,1,1,1,0.999068,0.999153,1,0.999713,0.999479] area_under_roc_curve 0.9990648383719539 [0.999964,0.999618,0.999894,0.999826,0.999618,0.996629,0.999541,0.999618,0.998315,0.997568] area_under_roc_curve 0.9997642953564815 [0.999612,0.999792,1,0.999653,0.999931,0.999859,0.999641,0.999792,1,0.999365] area_under_roc_curve 0.9996690780017193 [1,0.999583,1,0.999375,0.999896,0.999682,1,0.999305,0.999612,0.999259] area_under_roc_curve 0.9991169344729297 [1,0.999008,0.999677,0.999618,1,0.998341,1,0.999929,0.998271,0.99633] area_under_roc_curve 0.9997924974301545 [0.999824,0.999861,1,1,0.999753,0.999965,0.999541,1,0.999647,0.999329] 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 0.9644291920243431 [0.990826,0.964912,0.982143,0.974359,0.955752,0.990991,0.955752,0.973451,0.929825,0.925926] f_measure 0.9822040550205084 [1,0.982143,0.99115,0.964912,0.982759,0.982143,0.990991,0.981818,0.972973,0.973913] f_measure 0.9839340309063183 [0.990826,0.982759,0.990991,0.964912,0.99115,1,1,0.982759,0.990991,0.945455] f_measure 0.973400211077914 [1,0.965517,0.981818,0.964286,1,0.990991,0.99115,0.956522,0.981818,0.902655] f_measure 0.9838996000111957 [0.990826,0.974359,1,1,0.991304,0.981818,0.972477,0.991304,0.982143,0.954955] f_measure 0.9645518514763445 [0.990826,0.957983,0.990991,0.964286,0.964912,0.933333,0.990991,0.982456,0.945455,0.92437] f_measure 0.9768949388085576 [0.982143,0.964912,0.990991,0.964286,0.99115,0.973913,0.981481,0.965517,0.990991,0.964286] f_measure 0.9715549982069328 [0.99115,0.964912,1,0.982143,0.973451,0.964286,0.990991,0.938053,0.963636,0.948276] f_measure 0.9752076735747801 [0.99115,0.974359,0.990826,0.973913,0.990991,0.972477,1,0.990991,0.928571,0.93913] f_measure 0.9786548222262116 [0.982143,0.966102,0.990991,0.991304,0.973451,0.990991,0.972973,1,0.963636,0.954955] kappa 0.9604579003285794 kappa 0.9802291588245847 kappa 0.9822058673496311 kappa 0.9703433209148189 kappa 0.9822058673496311 kappa 0.9604556744699865 kappa 0.9742976352135766 kappa 0.9683668766864023 kappa 0.9723201407211961 kappa 0.976274656731855 kb_relative_information_score 0.9655836969730186 kb_relative_information_score 0.9806154588263274 kb_relative_information_score 0.9818207058116202 kb_relative_information_score 0.9727338318309506 kb_relative_information_score 0.9801796552522646 kb_relative_information_score 0.9633145478077594 kb_relative_information_score 0.9733532397854708 kb_relative_information_score 0.9715050696369597 kb_relative_information_score 0.9721408109350057 kb_relative_information_score 0.9760331968295851 mean_absolute_error 0.008211806885738835 mean_absolute_error 0.005500179963021083 mean_absolute_error 0.005412099836964022 mean_absolute_error 0.006987271499356426 mean_absolute_error 0.004989986795495081 mean_absolute_error 0.009152391577678921 mean_absolute_error 0.006993515356130328 mean_absolute_error 0.007368188621272235 mean_absolute_error 0.006758727801936489 mean_absolute_error 0.006119122491371277 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 0.9650157238875211 [1,0.964912,0.982143,0.966102,0.964286,1,0.947368,0.964912,0.898305,0.961538] precision 0.9826296847734874 [1,1,0.982456,0.982143,0.966102,0.982143,1,1,0.964286,0.949153] precision 0.9841270040731707 [1,0.966102,1,0.964912,1,1,1,0.966102,0.982143,0.962963] precision 0.9737364100255613 [1,0.949153,1,0.981818,1,1,0.982456,0.948276,0.981818,0.894737] precision 0.9843400402876541 [1,0.95,1,1,0.982759,0.981818,1,0.982759,0.964912,0.981481] precision 0.9658921322048402 [1,0.919355,1,0.981818,0.964912,0.98,1,0.982456,0.945455,0.887097] precision 0.9772877772146427 [0.982143,0.964912,0.982143,0.981818,1,0.949153,1,0.949153,1,0.964286] precision 0.9719933607248646 [0.982456,0.964912,1,1,0.982143,0.964286,0.982143,0.946429,0.981481,0.916667] precision 0.9756942388104808 [0.982456,0.966102,1,0.965517,1,1,1,1,0.928571,0.915254] precision 0.9790445581654686 [0.982143,0.934426,1,0.982759,0.964912,1,0.981818,1,0.981481,0.963636] predictive_accuracy 0.9644128113879004 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9644128113879004 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9786476868327402 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 0.045621966430873205 relative_absolute_error 0.030557102611909834 relative_absolute_error 0.030067696460687455 relative_absolute_error 0.038818788429615246 relative_absolute_error 0.027722625891150873 relative_absolute_error 0.05084749481629424 relative_absolute_error 0.03885338156148455 relative_absolute_error 0.040934927477972075 relative_absolute_error 0.037548922923723214 relative_absolute_error 0.03399535177445172 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 0.07038549652797087 root_mean_squared_error 0.05123540840838306 root_mean_squared_error 0.046903487388784575 root_mean_squared_error 0.06053457055871988 root_mean_squared_error 0.05344606412974509 root_mean_squared_error 0.07371436234095911 root_mean_squared_error 0.05881629724887724 root_mean_squared_error 0.06149669458412103 root_mean_squared_error 0.06305671863060004 root_mean_squared_error 0.0554185754382588 root_relative_squared_error 0.23462080479799804 root_relative_squared_error 0.17078650216173305 root_relative_squared_error 0.15634628318168736 root_relative_squared_error 0.20178361221640295 root_relative_squared_error 0.17815530742624205 root_relative_squared_error 0.24571696903072973 root_relative_squared_error 0.1960555040244205 root_relative_squared_error 0.20499021557763655 root_relative_squared_error 0.2101899579646 root_relative_squared_error 0.18472846394862402 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 0.9644065296470015 [0.981818,0.964912,0.982143,0.982759,0.947368,0.982143,0.964286,0.982143,0.963636,0.892857] unweighted_recall 0.9823577753160329 [1,0.964912,1,0.948276,1,0.982143,0.982143,0.964286,0.981818,1] unweighted_recall 0.9839900888585099 [0.981818,1,0.982143,0.964912,0.982456,1,1,1,1,0.928571] unweighted_recall 0.9733697881066302 [1,0.982456,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.910714] unweighted_recall 0.9839889496468442 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.929825] unweighted_recall 0.9642116655274551 [0.981818,1,0.982143,0.947368,0.964912,0.890909,0.982143,0.982456,0.945455,0.964912] unweighted_recall 0.9769400774663932 [0.982143,0.964912,1,0.947368,0.982456,1,0.963636,0.982456,0.982143,0.964286] unweighted_recall 0.9717418546365915 [1,0.964912,1,0.964912,0.964912,0.964286,1,0.929825,0.946429,0.982143] unweighted_recall 0.975060437143014 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.928571,0.964286] unweighted_recall 0.9785714285714284 [0.982143,1,0.982143,1,0.982143,0.982143,0.964286,1,0.946429,0.946429] usercpu_time_millis 10843.681037000351 usercpu_time_millis 11393.03854299942 usercpu_time_millis 11283.851340000183 usercpu_time_millis 12120.541254000273 usercpu_time_millis 12127.595354997538 usercpu_time_millis 12123.27744400136 usercpu_time_millis 10392.926326001543 usercpu_time_millis 10466.88653199999 usercpu_time_millis 10146.345024999391 usercpu_time_millis 10029.146426000807 usercpu_time_millis_testing 7.997900000191294 usercpu_time_millis_testing 7.813698999598273 usercpu_time_millis_testing 7.798200000252109 usercpu_time_millis_testing 9.188800000629271 usercpu_time_millis_testing 8.167700998455985 usercpu_time_millis_testing 8.005000001503504 usercpu_time_millis_testing 8.617700001195772 usercpu_time_millis_testing 7.793900000251597 usercpu_time_millis_testing 8.776599999691825 usercpu_time_millis_testing 8.123300000079325 usercpu_time_millis_training 10835.68313700016 usercpu_time_millis_training 11385.224843999822 usercpu_time_millis_training 11276.05313999993 usercpu_time_millis_training 12111.352453999643 usercpu_time_millis_training 12119.427653999082 usercpu_time_millis_training 12115.272443999856 usercpu_time_millis_training 10384.308626000347 usercpu_time_millis_training 10459.092631999738 usercpu_time_millis_training 10137.5684249997 usercpu_time_millis_training 10021.023126000728 wall_clock_time_millis 10845.544576644897 wall_clock_time_millis 11398.690938949585 wall_clock_time_millis 11295.344114303589 wall_clock_time_millis 12155.980110168457 wall_clock_time_millis 12130.40280342102 wall_clock_time_millis 12157.969951629639 wall_clock_time_millis 10408.38623046875 wall_clock_time_millis 10482.63931274414 wall_clock_time_millis 10167.82546043396 wall_clock_time_millis 10033.916473388672 wall_clock_time_millis_testing 8.002519607543945 wall_clock_time_millis_testing 7.816791534423828 wall_clock_time_millis_testing 7.802009582519531 wall_clock_time_millis_testing 9.195089340209961 wall_clock_time_millis_testing 8.170366287231445 wall_clock_time_millis_testing 8.008241653442383 wall_clock_time_millis_testing 8.622169494628906 wall_clock_time_millis_testing 7.799386978149414 wall_clock_time_millis_testing 8.781194686889648 wall_clock_time_millis_testing 8.130073547363281 wall_clock_time_millis_training 10837.542057037354 wall_clock_time_millis_training 11390.874147415161 wall_clock_time_millis_training 11287.54210472107 wall_clock_time_millis_training 12146.785020828247 wall_clock_time_millis_training 12122.232437133789 wall_clock_time_millis_training 12149.961709976196 wall_clock_time_millis_training 10399.764060974121 wall_clock_time_millis_training 10474.839925765991 wall_clock_time_millis_training 10159.04426574707 wall_clock_time_millis_training 10025.786399841309 weighted_recall 0.9644128113879004 [0.981818,0.964912,0.982143,0.982759,0.947368,0.982143,0.964286,0.982143,0.963636,0.892857] weighted_recall 0.9822064056939501 [1,0.964912,1,0.948276,1,0.982143,0.982143,0.964286,0.981818,1] weighted_recall 0.9839857651245552 [0.981818,1,0.982143,0.964912,0.982456,1,1,1,1,0.928571] weighted_recall 0.9733096085409253 [1,0.982456,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.910714] weighted_recall 0.9839857651245552 [0.981818,1,1,1,1,0.981818,0.946429,1,1,0.929825] weighted_recall 0.9644128113879004 [0.981818,1,0.982143,0.947368,0.964912,0.890909,0.982143,0.982456,0.945455,0.964912] weighted_recall 0.9768683274021353 [0.982143,0.964912,1,0.947368,0.982456,1,0.963636,0.982456,0.982143,0.964286] weighted_recall 0.9715302491103203 [1,0.964912,1,0.964912,0.964912,0.964286,1,0.929825,0.946429,0.982143] weighted_recall 0.9750889679715302 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.928571,0.964286] weighted_recall 0.9786476868327402 [0.982143,1,0.982143,1,0.982143,0.982143,0.964286,1,0.946429,0.946429]