10578647 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) 8294929 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 0.9344891939550843 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 146 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 97 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 5 19038 random_state 17155 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.15632138164538553 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 22083561 description https://api.openml.org/data/download/22083561/description.xml -1 22083562 predictions https://api.openml.org/data/download/22083562/predictions.arff area_under_roc_curve 0.9992246436791805 [0.999651,0.999601,0.999783,0.999232,0.999441,0.998986,0.999366,0.999736,0.998903,0.99754] average_cost 0 f_measure 0.973705454864435 [0.990975,0.977391,0.988257,0.967515,0.972687,0.977538,0.984698,0.977072,0.961226,0.940035] kappa 0.9707389069777203 kb_relative_information_score 0.9740847239071584 mean_absolute_error 0.005669068978854522 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9736654804270463 [0.990975,0.984238,0.982047,0.963287,0.971831,0.97491,0.980287,0.978799,0.962094,0.948399] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9737875804283169 [0.990975,0.970639,0.994545,0.971781,0.973545,0.98018,0.98915,0.975352,0.96036,0.931818] predictive_accuracy 0.9736654804270463 prior_entropy 3.3218327251668773 relative_absolute_error 0.03149528997177781 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.06588877851580847 root_relative_squared_error 0.2196308765417666 total_cost 0 unweighted_recall 0.9736865444230872 [0.990975,0.984238,0.982047,0.963287,0.971831,0.97491,0.980287,0.978799,0.962094,0.948399] area_under_roc_curve 0.9995952932167634 [1,0.999687,0.999965,0.999829,0.998645,1,0.999647,0.999859,0.999498,0.998835] area_under_roc_curve 0.9995948605998061 [0.999964,0.999896,0.999929,0.998426,0.999444,0.999929,0.999718,0.999929,0.999857,0.998906] area_under_roc_curve 0.9998029842114555 [1,1,1,0.999479,0.999931,1,1,1,0.999857,0.998765] area_under_roc_curve 0.9996271510250728 [1,0.999826,0.999541,0.999305,1,1,1,1,0.999606,0.997988] area_under_roc_curve 0.9997853037635882 [0.999928,1,1,0.999861,0.999965,0.999964,1,0.999896,0.999498,0.998749] area_under_roc_curve 0.9990191234116906 [0.999211,0.999722,0.999824,0.999375,0.998923,0.997382,0.999647,0.999931,0.998063,0.998055] area_under_roc_curve 0.9994336799129303 [0.999965,0.999965,1,0.999896,1,0.999894,0.999857,0.999201,0.999965,0.995589] area_under_roc_curve 0.9985744023508643 [0.999929,0.999236,0.999749,0.994789,0.999618,0.999541,1,0.999097,0.997741,0.996118] area_under_roc_curve 0.9991838183299283 [1,0.99935,0.999749,0.99934,0.999965,0.998094,1,0.999824,0.997494,0.998024] area_under_roc_curve 0.9986880801649715 [0.999965,0.998715,1,1,0.999612,0.999894,0.990824,0.999824,0.999118,0.998906] 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 0.9731368851003157 [1,0.965517,0.99115,0.983051,0.936937,0.99115,0.972973,0.990991,0.955752,0.944444] f_measure 0.9680024608264916 [0.981818,0.982143,0.982143,0.929825,0.964912,0.982456,0.990991,0.972973,0.964286,0.929825] f_measure 0.9839333961202741 [1,0.991304,0.990991,0.973913,0.982456,1,1,0.982759,0.962963,0.954955] f_measure 0.9767973763740116 [1,0.974359,0.981818,0.964912,0.982759,0.981818,0.99115,0.99115,0.972973,0.927273] f_measure 0.9804225721719483 [0.981481,0.982759,0.990991,0.982759,0.982759,0.990826,0.990991,0.982456,0.963636,0.955752] f_measure 0.9697346941773491 [0.981818,0.973913,0.981818,0.973913,0.956522,0.953271,0.972973,0.982456,0.954128,0.966102] f_measure 0.9804664043423569 [0.990991,0.99115,1,0.972973,1,0.965517,0.972477,0.965517,0.99115,0.954955] f_measure 0.9595678568580774 [0.99115,0.982143,0.981818,0.925926,0.972973,0.955752,0.990991,0.956522,0.954128,0.885246] f_measure 0.9734888754353112 [0.99115,0.982759,0.981481,0.964912,0.981818,0.981818,1,0.973451,0.946429,0.931034] f_measure 0.9715792230200073 [0.99115,0.949153,1,1,0.964912,0.972477,0.963636,0.972973,0.946429,0.954955] kappa 0.9703432165824691 kappa 0.964412861464856 kappa 0.9822056795474374 kappa 0.9742973639494672 kappa 0.9782510800579783 kappa 0.9663876780619264 kappa 0.9782519216900318 kappa 0.9545283450301655 kappa 0.9703432165824691 kappa 0.9683663202628635 kb_relative_information_score 0.9741816086578473 kb_relative_information_score 0.972595934526965 kb_relative_information_score 0.985544466033095 kb_relative_information_score 0.9804639158285272 kb_relative_information_score 0.9793942159627966 kb_relative_information_score 0.9678643483612344 kb_relative_information_score 0.9798104063661256 kb_relative_information_score 0.9570863635958412 kb_relative_information_score 0.9723622997515173 kb_relative_information_score 0.9715438927350303 mean_absolute_error 0.005610976864060947 mean_absolute_error 0.006561746061501355 mean_absolute_error 0.0032429694902238663 mean_absolute_error 0.004266686445489642 mean_absolute_error 0.004331059926014835 mean_absolute_error 0.006971795743840982 mean_absolute_error 0.00426557824952991 mean_absolute_error 0.009075652620319402 mean_absolute_error 0.005928290125148535 mean_absolute_error 0.006435934262415852 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 0.9736728289087674 [1,0.949153,0.982456,0.966667,0.962963,0.982456,0.981818,1,0.931034,0.980769] precision 0.968365334151094 [0.981818,1,0.982143,0.946429,0.964912,0.965517,1,0.981818,0.947368,0.913793] precision 0.9840665858766553 [1,0.982759,1,0.965517,0.982456,1,1,0.966102,0.981132,0.963636] precision 0.9771529246342024 [1,0.95,1,0.964912,0.966102,1,0.982456,1,0.964286,0.944444] precision 0.9807254013252565 [1,0.966102,1,0.966102,0.966102,1,1,0.982456,0.963636,0.964286] precision 0.9702314476409759 [0.981818,0.965517,1,0.965517,0.948276,0.980769,0.981818,0.982456,0.962963,0.934426] precision 0.9810160556702632 [1,1,1,1,1,0.933333,0.981481,0.949153,0.982456,0.963636] precision 0.9622485546355125 [0.982456,1,0.981818,0.980392,1,0.947368,0.982143,0.948276,0.981132,0.818182] precision 0.9741150028095149 [0.982456,0.982759,1,0.964912,1,1,1,0.964912,0.946429,0.9] precision 0.9721659759722203 [0.982456,0.918033,1,1,0.948276,1,0.981481,0.981818,0.946429,0.963636] predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9679715302491103 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9804270462633453 predictive_accuracy 0.9697508896797153 predictive_accuracy 0.9804270462633453 predictive_accuracy 0.9590747330960854 predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9715302491103204 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 0.031172651975188686 relative_absolute_error 0.03645479767255817 relative_absolute_error 0.018016781877774838 relative_absolute_error 0.023704188171051452 relative_absolute_error 0.024061858069336292 relative_absolute_error 0.0387328650589837 relative_absolute_error 0.02369797317511838 relative_absolute_error 0.05042096516849138 relative_absolute_error 0.03293532681030488 relative_absolute_error 0.035755428912658156 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 0.06604988122440737 root_mean_squared_error 0.06426394983051817 root_mean_squared_error 0.04970094153046699 root_mean_squared_error 0.05775790028257571 root_mean_squared_error 0.0606413475627431 root_mean_squared_error 0.07537443763321652 root_mean_squared_error 0.058131888559014425 root_mean_squared_error 0.0830336246716608 root_mean_squared_error 0.06902725785986799 root_mean_squared_error 0.0686831139906641 root_relative_squared_error 0.2201686008356044 root_relative_squared_error 0.2142154331857637 root_relative_squared_error 0.16567120936037155 root_relative_squared_error 0.1925279661767437 root_relative_squared_error 0.20213982252379595 root_relative_squared_error 0.25125060801534915 root_relative_squared_error 0.19377412799556296 root_relative_squared_error 0.2767804145693271 root_relative_squared_error 0.23009184022043988 root_relative_squared_error 0.2289435635320304 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 0.9733697881066302 [1,0.982456,1,1,0.912281,1,0.964286,0.982143,0.981818,0.910714] unweighted_recall 0.9682254028488148 [0.981818,0.964912,0.982143,0.913793,0.964912,1,0.982143,0.964286,0.981818,0.946429] unweighted_recall 0.9838938254727727 [1,1,0.982143,0.982456,0.982456,1,1,1,0.945455,0.946429] unweighted_recall 0.9768472317156529 [1,1,0.964286,0.964912,1,0.964286,1,0.982456,0.981818,0.910714] unweighted_recall 0.980320118478013 [0.963636,1,0.982143,1,1,0.981818,0.982143,0.982456,0.963636,0.947368] unweighted_recall 0.9695397584871269 [0.981818,0.982456,0.964286,0.982456,0.964912,0.927273,0.964286,0.982456,0.945455,1] unweighted_recall 0.9804488493962179 [0.982143,0.982456,1,0.947368,1,1,0.963636,0.982456,1,0.946429] unweighted_recall 0.9593347003873319 [1,0.964912,0.981818,0.877193,0.947368,0.964286,1,0.964912,0.928571,0.964286] unweighted_recall 0.9732735836456344 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.946429,0.964286] unweighted_recall 0.9714598997493734 [1,0.982456,1,1,0.982143,0.946429,0.946429,0.964286,0.946429,0.946429] usercpu_time_millis 5356.717668000783 usercpu_time_millis 3015.9322370000154 usercpu_time_millis 6314.427077999426 usercpu_time_millis 5609.440872998675 usercpu_time_millis 6330.500776999543 usercpu_time_millis 5703.860969000743 usercpu_time_millis 4522.319555999275 usercpu_time_millis 2731.4081360000273 usercpu_time_millis 4686.878761000116 usercpu_time_millis 2889.531236000039 usercpu_time_millis_testing 4.9641999994491925 usercpu_time_millis_testing 4.544400000668247 usercpu_time_millis_testing 4.680901000028825 usercpu_time_millis_testing 4.605500000252505 usercpu_time_millis_testing 5.0152000003436115 usercpu_time_millis_testing 4.589399999531452 usercpu_time_millis_testing 5.177301000003354 usercpu_time_millis_testing 3.7979999997332925 usercpu_time_millis_testing 4.515200000241748 usercpu_time_millis_testing 5.016799999793875 usercpu_time_millis_training 5351.753468001334 usercpu_time_millis_training 3011.387836999347 usercpu_time_millis_training 6309.746176999397 usercpu_time_millis_training 5604.835372998423 usercpu_time_millis_training 6325.485576999199 usercpu_time_millis_training 5699.271569001212 usercpu_time_millis_training 4517.142254999271 usercpu_time_millis_training 2727.610136000294 usercpu_time_millis_training 4682.363560999875 usercpu_time_millis_training 2884.514436000245 wall_clock_time_millis 5360.321521759033 wall_clock_time_millis 3016.401767730713 wall_clock_time_millis 6316.944122314453 wall_clock_time_millis 5614.232778549194 wall_clock_time_millis 6340.231895446777 wall_clock_time_millis 5716.985702514648 wall_clock_time_millis 4529.479742050171 wall_clock_time_millis 2739.020586013794 wall_clock_time_millis 4696.930408477783 wall_clock_time_millis 2890.9225463867188 wall_clock_time_millis_testing 4.96983528137207 wall_clock_time_millis_testing 4.548311233520508 wall_clock_time_millis_testing 4.683256149291992 wall_clock_time_millis_testing 4.611730575561523 wall_clock_time_millis_testing 5.018949508666992 wall_clock_time_millis_testing 4.593133926391602 wall_clock_time_millis_testing 5.180835723876953 wall_clock_time_millis_testing 3.7992000579833984 wall_clock_time_millis_testing 4.51970100402832 wall_clock_time_millis_testing 5.0201416015625 wall_clock_time_millis_training 5355.351686477661 wall_clock_time_millis_training 3011.8534564971924 wall_clock_time_millis_training 6312.260866165161 wall_clock_time_millis_training 5609.621047973633 wall_clock_time_millis_training 6335.21294593811 wall_clock_time_millis_training 5712.392568588257 wall_clock_time_millis_training 4524.298906326294 wall_clock_time_millis_training 2735.2213859558105 wall_clock_time_millis_training 4692.410707473755 wall_clock_time_millis_training 2885.9024047851562 weighted_recall 0.9733096085409253 [1,0.982456,1,1,0.912281,1,0.964286,0.982143,0.981818,0.910714] weighted_recall 0.9679715302491103 [0.981818,0.964912,0.982143,0.913793,0.964912,1,0.982143,0.964286,0.981818,0.946429] weighted_recall 0.9839857651245552 [1,1,0.982143,0.982456,0.982456,1,1,1,0.945455,0.946429] weighted_recall 0.9768683274021353 [1,1,0.964286,0.964912,1,0.964286,1,0.982456,0.981818,0.910714] weighted_recall 0.9804270462633452 [0.963636,1,0.982143,1,1,0.981818,0.982143,0.982456,0.963636,0.947368] weighted_recall 0.9697508896797153 [0.981818,0.982456,0.964286,0.982456,0.964912,0.927273,0.964286,0.982456,0.945455,1] weighted_recall 0.9804270462633452 [0.982143,0.982456,1,0.947368,1,1,0.963636,0.982456,1,0.946429] weighted_recall 0.9590747330960854 [1,0.964912,0.981818,0.877193,0.947368,0.964286,1,0.964912,0.928571,0.964286] weighted_recall 0.9733096085409253 [1,0.982759,0.963636,0.964912,0.964286,0.964286,1,0.982143,0.946429,0.964286] weighted_recall 0.9715302491103203 [1,0.982456,1,1,0.982143,0.946429,0.946429,0.964286,0.946429,0.946429]