10578884 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) 8295166 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 0.9271983347357825 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 992 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 46 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 16 19038 random_state 8824 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.028574955340301196 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 22084035 description https://api.openml.org/data/download/22084035/description.xml -1 22084036 predictions https://api.openml.org/data/download/22084036/predictions.arff area_under_roc_curve 0.9340051932705726 [0.95137,0.946698,0.8943,0.941129,0.908509,0.947581,0.872655,0.967352,0.949796,0.960145] average_cost 0 f_measure 0.9057772311347252 [0.947464,0.914729,0.874776,0.917186,0.898106,0.918969,0.886006,0.94026,0.878261,0.881385] kappa 0.8952145675743439 kb_relative_information_score 0.9022033101042336 mean_absolute_error 0.019721571529181033 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.905693950177936 [0.944043,0.929947,0.877917,0.90035,0.876761,0.894265,0.856631,0.959364,0.911552,0.905694] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9068679192420055 [0.950909,0.9,0.871658,0.934664,0.920518,0.945076,0.917466,0.921902,0.847315,0.858347] predictive_accuracy 0.905693950177936 prior_entropy 3.3218327251668773 relative_absolute_error 0.10956589456355836 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.13318194088764468 root_relative_squared_error 0.44394306702269615 total_cost 0 unweighted_recall 0.9056524722039917 [0.944043,0.929947,0.877917,0.90035,0.876761,0.894265,0.856631,0.959364,0.911552,0.905694] area_under_roc_curve 0.9994156720462735 [1,0.999618,0.999929,0.999726,0.997533,1,0.999541,0.999929,0.999498,0.998412] area_under_roc_curve 0.8496893145102866 [0.927093,0.967553,0.641675,0.849702,0.700208,0.726355,0.984331,0.903021,0.85069,0.948228] area_under_roc_curve 0.9998381773261605 [1,1,1,0.999653,0.999965,0.999929,1,1,0.999928,0.998906] area_under_roc_curve 0.8048820139231384 [0.861646,0.869515,0.578928,0.821522,0.950165,0.924795,0.308371,0.976238,0.834463,0.917614] area_under_roc_curve 0.9998664829169929 [0.999785,0.999826,1,1,1,0.999892,0.999929,1,0.99939,0.999826] area_under_roc_curve 0.8281056598619788 [0.793814,0.855029,0.840009,0.807817,0.635626,0.902349,0.82367,0.8963,0.873534,0.856036] area_under_roc_curve 0.9998943720768487 [0.999965,1,1,0.999583,1,0.999929,1,0.999757,1,0.999718] area_under_roc_curve 0.9996622120822635 [1,0.999722,1,0.999618,0.999861,0.999753,1,0.999792,0.999788,0.998094] area_under_roc_curve 0.9989831460894452 [1,0.998529,0.999606,0.999722,0.999965,0.996294,1,0.999718,0.997847,0.998165] area_under_roc_curve 0.8921781927535165 [0.967215,0.804273,0.932789,0.967605,0.847014,0.942723,0.687112,0.91045,0.951828,0.910997] 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 0.9714178525868359 [1,0.964912,0.99115,0.974359,0.955752,1,0.964286,0.982143,0.947368,0.934579] f_measure 0.8028432740250904 [0.847458,0.938053,0.701031,0.766667,0.727273,0.745098,0.933333,0.8,0.743802,0.825688] f_measure 0.9910532308772395 [1,1,1,0.991304,0.982456,0.982143,1,0.991304,0.990991,0.972477] f_measure 0.7341438859151094 [0.87037,0.753846,0.565657,0.796117,0.912281,0.762887,0.318182,0.933333,0.733333,0.689655] f_measure 0.9875404145670984 [0.990826,0.982759,1,1,0.982759,0.990826,0.981818,0.991304,0.972477,0.982456] f_measure 0.7641380917192211 [0.811881,0.744186,0.727273,0.754717,0.594595,0.851852,0.811881,0.900901,0.68254,0.763636] f_measure 0.9893376508512668 [0.990991,1,0.990991,0.982143,1,0.973913,1,0.982456,1,0.972973] f_measure 0.9768295724853499 [0.99115,0.964912,1,0.963636,0.982143,0.972973,0.982143,0.974359,0.972973,0.964912] f_measure 0.9769271162926538 [0.99115,0.982759,0.963636,0.964912,0.981818,0.981818,1,0.973451,0.972973,0.956522] f_measure 0.8531505916860584 [0.972973,0.851485,0.781955,0.964286,0.830189,0.890909,0.72549,0.884956,0.817391,0.809917] kappa 0.9683664315491372 kappa 0.7845145086341235 kappa 0.9901144403049396 kappa 0.7152938775940982 kappa 0.9861597782187135 kappa 0.7350735242383732 kappa 0.9881374952947509 kappa 0.9742980873077018 kappa 0.9742976352135766 kappa 0.8359112543224294 kb_relative_information_score 0.9708504979554671 kb_relative_information_score 0.8004342870669968 kb_relative_information_score 0.9895043577060595 kb_relative_information_score 0.7298624220829456 kb_relative_information_score 0.9860740838423393 kb_relative_information_score 0.7558779157037876 kb_relative_information_score 0.9883342256020522 kb_relative_information_score 0.9768534292426105 kb_relative_information_score 0.9759053231834315 kb_relative_information_score 0.8483350846537947 mean_absolute_error 0.00605936085662369 mean_absolute_error 0.04037845885577155 mean_absolute_error 0.0023376078729798384 mean_absolute_error 0.053555733521342797 mean_absolute_error 0.0031065656495160255 mean_absolute_error 0.048542257375499324 mean_absolute_error 0.002333060846202025 mean_absolute_error 0.004833900469282579 mean_absolute_error 0.0050441162842732624 mean_absolute_error 0.031024653560318378 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 0.9719869603455175 [1,0.964912,0.982456,0.966102,0.964286,1,0.964286,0.982143,0.915254,0.980392] precision 0.8128352260775638 [0.793651,0.946429,0.829268,0.741935,0.857143,0.826087,0.875,0.724638,0.681818,0.849057] precision 0.9911963343442666 [1,1,1,0.982759,0.982456,0.982143,1,0.982759,0.982143,1] precision 0.7485729864840086 [0.886792,0.671233,0.651163,0.891304,0.912281,0.902439,0.4375,0.888889,0.676923,0.561798] precision 0.9877834805714071 [1,0.966102,1,1,0.966102,1,1,0.982759,0.981481,0.982456] precision 0.7763503497306877 [0.891304,0.666667,0.676923,0.816327,0.611111,0.867925,0.911111,0.925926,0.605634,0.792453] precision 0.9895946934120226 [1,1,0.982143,1,1,0.949153,1,0.982456,1,0.981818] precision 0.9774106831632456 [0.982456,0.964912,1,1,1,0.981818,0.964912,0.95,0.981818,0.948276] precision 0.9772915295218398 [0.982456,0.982759,0.963636,0.964912,1,1,1,0.964912,0.981818,0.932203] precision 0.8639765765450536 [0.981818,0.977273,0.675325,0.981818,0.88,0.907407,0.804348,0.877193,0.79661,0.753846] predictive_accuracy 0.9715302491103204 predictive_accuracy 0.806049822064057 predictive_accuracy 0.9911032028469751 predictive_accuracy 0.7437722419928825 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.7615658362989324 predictive_accuracy 0.98932384341637 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.8523131672597865 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 0.03366371876980168 relative_absolute_error 0.2243287890327273 relative_absolute_error 0.012986915630939101 relative_absolute_error 0.2975365547122859 relative_absolute_error 0.017258995030925386 relative_absolute_error 0.2696838481311876 relative_absolute_error 0.012961622109571596 relative_absolute_error 0.026855360973597225 relative_absolute_error 0.028023192992356824 relative_absolute_error 0.17236033646176696 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 0.07188780783037478 root_mean_squared_error 0.19044509849244218 root_mean_squared_error 0.04098224477240845 root_mean_squared_error 0.2225828419615321 root_mean_squared_error 0.047724788775295214 root_mean_squared_error 0.21100320015873286 root_mean_squared_error 0.045950027990710136 root_mean_squared_error 0.06457099875598045 root_mean_squared_error 0.06550692377893633 root_mean_squared_error 0.1653555365046616 root_relative_squared_error 0.2396285621374247 root_relative_squared_error 0.63482371343895 root_relative_squared_error 0.13660864049397575 root_relative_squared_error 0.741949095431734 root_relative_squared_error 0.15908420113920438 root_relative_squared_error 0.7033509502391719 root_relative_squared_error 0.15316768173173087 root_relative_squared_error 0.2152379578213866 root_relative_squared_error 0.21835734326973275 root_relative_squared_error 0.5511847611084403 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 0.9716143218547936 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.982143,0.981818,0.892857] unweighted_recall 0.8063922541463378 [0.909091,0.929825,0.607143,0.793103,0.631579,0.678571,1,0.892857,0.818182,0.803571] unweighted_recall 0.9911027568922306 [1,1,1,1,0.982456,0.982143,1,1,1,0.946429] unweighted_recall 0.7431801093643198 [0.854545,0.859649,0.5,0.719298,0.912281,0.660714,0.25,0.982456,0.8,0.892857] unweighted_recall 0.9874014581909318 [0.981818,1,1,1,1,0.981818,0.964286,1,0.963636,0.982456] unweighted_recall 0.7618335611756664 [0.745455,0.842105,0.785714,0.701754,0.578947,0.836364,0.732143,0.877193,0.781818,0.736842] unweighted_recall 0.9893796992481201 [0.982143,1,1,0.964912,1,1,1,0.982456,1,0.964286] unweighted_recall 0.9770363408521303 [1,0.964912,1,0.929825,0.964912,0.964286,1,1,0.964286,0.982143] unweighted_recall 0.9768450122170631 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.964286,0.982143] unweighted_recall 0.8523182957393484 [0.964286,0.754386,0.928571,0.947368,0.785714,0.875,0.660714,0.892857,0.839286,0.875] usercpu_time_millis 6923.430383998493 usercpu_time_millis 2866.04233899925 usercpu_time_millis 8373.666801999207 usercpu_time_millis 2896.291035001923 usercpu_time_millis 8278.308503999142 usercpu_time_millis 2878.303940000478 usercpu_time_millis 14888.330590001715 usercpu_time_millis 10640.188034001767 usercpu_time_millis 8060.975000998951 usercpu_time_millis 2897.5365350015636 usercpu_time_millis_testing 5.859599999894272 usercpu_time_millis_testing 4.133799999181065 usercpu_time_millis_testing 5.093299998407019 usercpu_time_millis_testing 4.114000001209206 usercpu_time_millis_testing 5.163499999980559 usercpu_time_millis_testing 4.212200999972993 usercpu_time_millis_testing 8.140501000525546 usercpu_time_millis_testing 6.016900000759051 usercpu_time_millis_testing 5.18489999922167 usercpu_time_millis_testing 3.7295000001904555 usercpu_time_millis_training 6917.570783998599 usercpu_time_millis_training 2861.908539000069 usercpu_time_millis_training 8368.5735020008 usercpu_time_millis_training 2892.1770350007137 usercpu_time_millis_training 8273.145003999161 usercpu_time_millis_training 2874.091739000505 usercpu_time_millis_training 14880.19008900119 usercpu_time_millis_training 10634.171134001008 usercpu_time_millis_training 8055.7901009997295 usercpu_time_millis_training 2893.807035001373 wall_clock_time_millis 6923.692464828491 wall_clock_time_millis 2866.337776184082 wall_clock_time_millis 8387.866020202637 wall_clock_time_millis 2903.9599895477295 wall_clock_time_millis 8281.589984893799 wall_clock_time_millis 2881.2882900238037 wall_clock_time_millis 14904.705047607422 wall_clock_time_millis 10656.584978103638 wall_clock_time_millis 8071.241617202759 wall_clock_time_millis 2900.615453720093 wall_clock_time_millis_testing 5.863428115844727 wall_clock_time_millis_testing 4.137516021728516 wall_clock_time_millis_testing 5.096435546875 wall_clock_time_millis_testing 4.118204116821289 wall_clock_time_millis_testing 5.166292190551758 wall_clock_time_millis_testing 4.358053207397461 wall_clock_time_millis_testing 8.143186569213867 wall_clock_time_millis_testing 6.019353866577148 wall_clock_time_millis_testing 5.188226699829102 wall_clock_time_millis_testing 3.7326812744140625 wall_clock_time_millis_training 6917.8290367126465 wall_clock_time_millis_training 2862.2002601623535 wall_clock_time_millis_training 8382.769584655762 wall_clock_time_millis_training 2899.841785430908 wall_clock_time_millis_training 8276.423692703247 wall_clock_time_millis_training 2876.9302368164062 wall_clock_time_millis_training 14896.561861038208 wall_clock_time_millis_training 10650.56562423706 wall_clock_time_millis_training 8066.05339050293 wall_clock_time_millis_training 2896.8827724456787 weighted_recall 0.9715302491103203 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.982143,0.981818,0.892857] weighted_recall 0.806049822064057 [0.909091,0.929825,0.607143,0.793103,0.631579,0.678571,1,0.892857,0.818182,0.803571] weighted_recall 0.9911032028469751 [1,1,1,1,0.982456,0.982143,1,1,1,0.946429] weighted_recall 0.7437722419928826 [0.854545,0.859649,0.5,0.719298,0.912281,0.660714,0.25,0.982456,0.8,0.892857] weighted_recall 0.9875444839857651 [0.981818,1,1,1,1,0.981818,0.964286,1,0.963636,0.982456] weighted_recall 0.7615658362989324 [0.745455,0.842105,0.785714,0.701754,0.578947,0.836364,0.732143,0.877193,0.781818,0.736842] weighted_recall 0.9893238434163701 [0.982143,1,1,0.964912,1,1,1,0.982456,1,0.964286] weighted_recall 0.9768683274021353 [1,0.964912,1,0.929825,0.964912,0.964286,1,1,0.964286,0.982143] weighted_recall 0.9768683274021353 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.964286,0.982143] weighted_recall 0.8523131672597865 [0.964286,0.754386,0.928571,0.947368,0.785714,0.875,0.660714,0.892857,0.839286,0.875]