10578607 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) 8294889 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 0.11897476448102996 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1084 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 171 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 14847 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.3799599358839793 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 22083481 description https://api.openml.org/data/download/22083481/description.xml -1 22083482 predictions https://api.openml.org/data/download/22083482/predictions.arff area_under_roc_curve 0.9995071626454518 [0.999967,0.999659,0.999837,0.999643,0.999657,0.998919,0.999817,0.999812,0.999415,0.998343] average_cost 0 f_measure 0.9781656269592097 [0.991855,0.975652,0.991928,0.974449,0.977935,0.981098,0.987455,0.98227,0.971014,0.948381] kappa 0.9756817139301185 kb_relative_information_score 0.973192282952486 mean_absolute_error 0.00737341181926346 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9781138790035587 [0.98917,0.982487,0.992819,0.966783,0.975352,0.976703,0.987455,0.978799,0.967509,0.964413] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9783038012747056 [0.994555,0.968912,0.991039,0.982238,0.980531,0.985533,0.987455,0.985765,0.974545,0.932874] predictive_accuracy 0.9781138790035587 prior_entropy 3.3218327251668773 relative_absolute_error 0.040964000296210855 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.059089481704310796 root_relative_squared_error 0.19696638719752138 total_cost 0 unweighted_recall 0.9781488670476893 [0.98917,0.982487,0.992819,0.966783,0.975352,0.976703,0.987455,0.978799,0.967509,0.964413] area_under_roc_curve 0.9993629866593643 [1,0.999722,0.999929,0.999487,0.998159,1,0.999824,0.999788,0.999426,0.997318] area_under_roc_curve 0.9996692441596214 [1,0.999826,1,0.999487,0.999514,0.999612,1,0.999894,0.999283,0.999082] area_under_roc_curve 0.9997396312430252 [1,1,1,0.999583,0.999722,1,1,0.999965,1,0.99813] area_under_roc_curve 0.9996340240727501 [1,0.999792,0.999435,0.998888,1,1,1,0.999861,0.999821,0.998553] area_under_roc_curve 0.9997501594751403 [0.999857,0.999514,1,1,1,0.999821,0.999471,1,0.999749,0.999097] area_under_roc_curve 0.9989351018421824 [0.999964,0.999757,1,0.999687,0.999375,0.995804,0.999541,0.999861,0.997454,0.997811] area_under_roc_curve 0.9998311719737473 [0.999894,0.999757,1,0.999965,0.999965,0.999824,0.999713,0.999861,0.999859,0.999471] area_under_roc_curve 0.9995320728835152 [0.999965,0.999792,0.999928,0.999757,0.999722,0.9994,0.999964,0.999479,1,0.997318] area_under_roc_curve 0.9989447083319445 [1,0.999111,0.999319,0.999479,1,0.9964,1,0.999612,0.998518,0.997] area_under_roc_curve 0.9998593113218175 [0.999929,0.999931,1,0.999931,1,0.999929,0.999612,1,0.999788,0.999471] 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 0.9769145582688661 [1,0.973913,0.982143,0.982456,0.973451,1,0.973451,0.973451,0.946429,0.963636] f_measure 0.9752164042056777 [0.990826,0.964912,1,0.964286,0.964912,0.973451,1,0.981818,0.963636,0.949153] f_measure 0.9892555648454789 [1,1,1,0.973913,0.973913,1,1,0.991304,1,0.954128] f_measure 0.9840299107497206 [1,0.973913,0.981818,0.972973,1,1,0.99115,0.99115,0.982143,0.947368] f_measure 0.9840437527881644 [0.981481,0.974359,1,1,0.99115,0.981818,0.981818,1,0.972973,0.956522] f_measure 0.968013459116211 [0.981818,0.982759,1,0.964912,0.948276,0.952381,0.982143,0.982143,0.944444,0.941176] f_measure 0.9769742815467869 [0.990991,0.964286,0.990991,0.982143,0.982456,0.973451,0.981818,0.973913,0.990991,0.93913] f_measure 0.9751567344117654 [0.99115,0.982143,0.990991,0.973451,0.964286,0.982143,0.990991,0.946429,0.990991,0.940171] f_measure 0.9715843403535629 [1,0.966102,0.981818,0.956522,0.990991,0.963636,1,0.982143,0.945455,0.929825] f_measure 0.9804210451491027 [0.982143,0.974359,0.99115,0.973913,0.990991,0.982143,0.972973,1,0.972477,0.964286] kappa 0.9742979968901491 kappa 0.9723210171006019 kappa 0.9881372448997541 kappa 0.9822063681361012 kappa 0.9822056795474374 kappa 0.9644101070229878 kappa 0.9742979968901491 kappa 0.9723214065847472 kappa 0.9683657638197496 kappa 0.9782518451807186 kb_relative_information_score 0.9707340170275129 kb_relative_information_score 0.9747661391584589 kb_relative_information_score 0.9793054644852794 kb_relative_information_score 0.9748903011783027 kb_relative_information_score 0.9771264302198058 kb_relative_information_score 0.9609036477638849 kb_relative_information_score 0.9757043730306587 kb_relative_information_score 0.9713748080806233 kb_relative_information_score 0.967665572596814 kb_relative_information_score 0.979451883945233 mean_absolute_error 0.007916822886361762 mean_absolute_error 0.006974273358771771 mean_absolute_error 0.0062097115698388035 mean_absolute_error 0.0073343256128146055 mean_absolute_error 0.00636930852514602 mean_absolute_error 0.0102301097233971 mean_absolute_error 0.006624089768500827 mean_absolute_error 0.007571990971010991 mean_absolute_error 0.00849683437674664 mean_absolute_error 0.006006651400046211 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 0.9772066101325908 [1,0.965517,0.982143,1,0.982143,1,0.964912,0.964912,0.929825,0.981481] precision 0.9761845780793391 [1,0.964912,1,1,0.964912,0.964912,1,1,0.963636,0.903226] precision 0.9893765180123965 [1,1,1,0.965517,0.965517,1,1,0.982759,1,0.981132] precision 0.9844486353938595 [1,0.965517,1,1,1,1,0.982456,1,0.964912,0.931034] precision 0.9844082534228563 [1,0.95,1,1,1,0.981818,1,1,0.964286,0.948276] precision 0.9690601229539808 [0.981818,0.966102,1,0.964912,0.932203,1,0.982143,1,0.962264,0.903226] precision 0.9774115681006192 [1,0.981818,0.982143,1,0.982456,0.964912,0.981818,0.965517,1,0.915254] precision 0.9758329419432453 [0.982456,1,0.982143,0.982143,0.981818,0.982143,0.982143,0.963636,1,0.901639] precision 0.9719093003913227 [1,0.95,0.981818,0.948276,1,0.981481,1,0.982143,0.962963,0.913793] precision 0.9807541722421496 [0.982143,0.95,0.982456,0.965517,1,0.982143,0.981818,1,1,0.964286] predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9750889679715303 predictive_accuracy 0.98932384341637 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9679715302491103 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9804270462633453 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 0.04398313708375386 relative_absolute_error 0.038746657036734695 relative_absolute_error 0.03449894277912474 relative_absolute_error 0.04074689730662134 relative_absolute_error 0.0353856562480988 relative_absolute_error 0.05683492087458016 relative_absolute_error 0.03680098979799714 relative_absolute_error 0.042067177863407475 relative_absolute_error 0.0472051824629909 relative_absolute_error 0.033370508209145784 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 0.062270424652328814 root_mean_squared_error 0.057056722985041275 root_mean_squared_error 0.04899739375616958 root_mean_squared_error 0.055486928585786806 root_mean_squared_error 0.05326323262544569 root_mean_squared_error 0.07337127675918106 root_mean_squared_error 0.05518858628865251 root_mean_squared_error 0.06234926403148143 root_mean_squared_error 0.0669274132361879 root_mean_squared_error 0.0516743997604891 root_relative_squared_error 0.20757027893149213 root_relative_squared_error 0.1901910894464886 root_relative_squared_error 0.16332603023455566 root_relative_squared_error 0.184957996356362 root_relative_squared_error 0.17754586305674475 root_relative_squared_error 0.24457333912475945 root_relative_squared_error 0.18396306138471744 root_relative_squared_error 0.207832130838143 root_relative_squared_error 0.22309232830848758 root_relative_squared_error 0.17224788652059608 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 0.9769379168925447 [1,0.982456,0.982143,0.965517,0.964912,1,0.982143,0.982143,0.963636,0.946429] unweighted_recall 0.9752742161045246 [0.981818,0.964912,1,0.931034,0.964912,0.982143,1,0.964286,0.963636,1] unweighted_recall 0.9893483709273182 [1,1,1,0.982456,0.982456,1,1,1,1,0.928571] unweighted_recall 0.9840852130325815 [1,0.982456,0.964286,0.947368,1,1,1,0.982456,1,0.964286] unweighted_recall 0.9838926862611075 [0.963636,1,1,1,0.982456,0.981818,0.964286,1,0.981818,0.964912] unweighted_recall 0.9677517657780814 [0.981818,1,1,0.964912,0.964912,0.909091,0.982143,0.964912,0.927273,0.982456] unweighted_recall 0.9769725449988605 [0.982143,0.947368,1,0.964912,0.982456,0.982143,0.981818,0.982456,0.982143,0.964286] unweighted_recall 0.975344611528822 [1,0.964912,1,0.964912,0.947368,0.982143,1,0.929825,0.982143,0.982143] unweighted_recall 0.9715203368923875 [1,0.982759,0.981818,0.964912,0.982143,0.946429,1,0.982143,0.928571,0.946429] unweighted_recall 0.9803884711779448 [0.982143,1,1,0.982456,0.982143,0.982143,0.964286,1,0.946429,0.964286] usercpu_time_millis 10477.857427002164 usercpu_time_millis 10516.722329000913 usercpu_time_millis 10481.325028000356 usercpu_time_millis 10479.715528999805 usercpu_time_millis 10538.86802299894 usercpu_time_millis 10512.797927000065 usercpu_time_millis 10530.758231998334 usercpu_time_millis 10573.321632000443 usercpu_time_millis 10610.89414000162 usercpu_time_millis 10449.153931000183 usercpu_time_millis_testing 10.279300000547664 usercpu_time_millis_testing 10.562400000708294 usercpu_time_millis_testing 9.375999999974738 usercpu_time_millis_testing 10.099899998749606 usercpu_time_millis_testing 8.925699999963399 usercpu_time_millis_testing 9.986799999751383 usercpu_time_millis_testing 9.546299999783514 usercpu_time_millis_testing 8.431701000517933 usercpu_time_millis_testing 8.333700001458055 usercpu_time_millis_testing 10.094600000229548 usercpu_time_millis_training 10467.578127001616 usercpu_time_millis_training 10506.159929000205 usercpu_time_millis_training 10471.949028000381 usercpu_time_millis_training 10469.615629001055 usercpu_time_millis_training 10529.942322998977 usercpu_time_millis_training 10502.811127000314 usercpu_time_millis_training 10521.21193199855 usercpu_time_millis_training 10564.889930999925 usercpu_time_millis_training 10602.560440000161 usercpu_time_millis_training 10439.059330999953 wall_clock_time_millis 10490.641117095947 wall_clock_time_millis 10524.450778961182 wall_clock_time_millis 10487.125873565674 wall_clock_time_millis 10480.29375076294 wall_clock_time_millis 10568.016052246094 wall_clock_time_millis 10527.4977684021 wall_clock_time_millis 10541.889190673828 wall_clock_time_millis 10581.63046836853 wall_clock_time_millis 10668.228387832642 wall_clock_time_millis 10473.692655563354 wall_clock_time_millis_testing 10.28585433959961 wall_clock_time_millis_testing 10.569334030151367 wall_clock_time_millis_testing 9.382486343383789 wall_clock_time_millis_testing 10.104894638061523 wall_clock_time_millis_testing 8.927345275878906 wall_clock_time_millis_testing 9.991168975830078 wall_clock_time_millis_testing 9.549140930175781 wall_clock_time_millis_testing 8.436203002929688 wall_clock_time_millis_testing 8.336544036865234 wall_clock_time_millis_testing 10.099411010742188 wall_clock_time_millis_training 10480.355262756348 wall_clock_time_millis_training 10513.88144493103 wall_clock_time_millis_training 10477.74338722229 wall_clock_time_millis_training 10470.188856124878 wall_clock_time_millis_training 10559.088706970215 wall_clock_time_millis_training 10517.50659942627 wall_clock_time_millis_training 10532.340049743652 wall_clock_time_millis_training 10573.1942653656 wall_clock_time_millis_training 10659.891843795776 wall_clock_time_millis_training 10463.593244552612 weighted_recall 0.9768683274021353 [1,0.982456,0.982143,0.965517,0.964912,1,0.982143,0.982143,0.963636,0.946429] weighted_recall 0.9750889679715302 [0.981818,0.964912,1,0.931034,0.964912,0.982143,1,0.964286,0.963636,1] weighted_recall 0.9893238434163701 [1,1,1,0.982456,0.982456,1,1,1,1,0.928571] weighted_recall 0.9839857651245552 [1,0.982456,0.964286,0.947368,1,1,1,0.982456,1,0.964286] weighted_recall 0.9839857651245552 [0.963636,1,1,1,0.982456,0.981818,0.964286,1,0.981818,0.964912] weighted_recall 0.9679715302491103 [0.981818,1,1,0.964912,0.964912,0.909091,0.982143,0.964912,0.927273,0.982456] weighted_recall 0.9768683274021353 [0.982143,0.947368,1,0.964912,0.982456,0.982143,0.981818,0.982456,0.982143,0.964286] weighted_recall 0.9750889679715302 [1,0.964912,1,0.964912,0.947368,0.982143,1,0.929825,0.982143,0.982143] weighted_recall 0.9715302491103203 [1,0.982759,0.981818,0.964912,0.982143,0.946429,1,0.982143,0.928571,0.946429] weighted_recall 0.9804270462633452 [0.982143,1,1,0.982456,0.982143,0.982143,0.964286,1,0.946429,0.964286]