10578931 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) 8295213 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 0.10876026493456056 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1921 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 115 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 10 19038 random_state 21429 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.061550090691122265 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 22084129 description https://api.openml.org/data/download/22084129/description.xml -1 22084130 predictions https://api.openml.org/data/download/22084130/predictions.arff area_under_roc_curve 0.999622067594544 [0.999969,0.999647,0.99994,0.999576,0.999717,0.999646,0.999697,0.99987,0.999404,0.998759] average_cost 0 f_measure 0.9795487488028111 [0.993677,0.97747,0.990991,0.975352,0.978947,0.981132,0.987433,0.981432,0.972047,0.957371] kappa 0.977263335881988 kb_relative_information_score 0.9750663997958736 mean_absolute_error 0.00694783333457751 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9795373665480427 [0.99278,0.987741,0.987433,0.968531,0.982394,0.978495,0.985663,0.980565,0.972924,0.959075] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9795995666874375 [0.994575,0.96741,0.994575,0.98227,0.975524,0.983784,0.989209,0.982301,0.971171,0.955674] predictive_accuracy 0.9795373665480427 prior_entropy 3.3218327251668773 relative_absolute_error 0.038599640675446086 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.056390333090331354 root_relative_squared_error 0.18796915899936065 total_cost 0 unweighted_recall 0.9795601096710882 [0.99278,0.987741,0.987433,0.968531,0.982394,0.978495,0.985663,0.980565,0.972924,0.959075] area_under_roc_curve 0.999595230793811 [1,0.999861,0.999965,0.999932,0.998159,1,0.999682,0.999894,0.999713,0.998765] area_under_roc_curve 0.9998204129019379 [1,1,1,0.999282,0.999931,0.999894,1,0.999965,0.999677,0.999471] area_under_roc_curve 0.9998487338514094 [1,1,0.999965,0.999687,0.999965,1,1,1,0.999928,0.998941] area_under_roc_curve 0.9995846744337038 [1,0.999618,0.999718,0.998402,1,1,1,0.999965,0.999857,0.998306] area_under_roc_curve 0.9997994811232128 [0.999785,0.999965,1,1,0.999965,0.999713,0.999929,1,0.999713,0.998923] area_under_roc_curve 0.9994198623705457 [0.999964,0.999896,1,0.999653,0.999409,0.998781,0.999506,0.999826,0.998315,0.998819] area_under_roc_curve 0.9998030051291461 [0.999894,0.999861,1,0.999965,1,0.999824,0.999892,0.999722,0.999894,0.998977] area_under_roc_curve 0.9996972728098256 [1,0.999305,0.999964,0.999687,0.999826,0.999647,1,0.999618,0.999894,0.999047] area_under_roc_curve 0.9990605655813073 [1,0.998837,0.999713,0.999479,1,0.998447,1,0.999753,0.997741,0.996647] area_under_roc_curve 0.9996482783045442 [0.999894,0.999687,1,0.999965,1,0.999894,0.998518,1,0.999259,0.999259] 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 0.9786298117049472 [1,0.973913,0.982143,0.982759,0.964286,1,0.973451,0.982143,0.964286,0.963636] f_measure 0.9822358075406401 [1,0.99115,1,0.973913,0.973913,0.973913,1,0.981818,0.981818,0.946429] f_measure 0.9875246330524625 [1,0.991304,0.990991,0.973913,0.982456,1,1,0.982759,0.981818,0.972477] f_measure 0.9804862978346788 [1,0.965517,0.981818,0.964286,1,1,0.99115,0.982143,0.972973,0.947368] f_measure 0.9802899459336928 [0.990826,0.982759,1,0.991304,0.974359,0.981818,0.972477,0.991304,0.972973,0.945455] f_measure 0.9716659580166979 [0.981818,0.974359,0.990991,0.982143,0.948276,0.962264,0.990991,0.973451,0.963636,0.949153] f_measure 0.9822036031487401 [0.990991,0.991304,0.990991,0.972973,1,0.964912,0.981818,0.973913,0.982143,0.972973] f_measure 0.9732588594621064 [0.99115,0.973451,0.981818,0.954955,0.973451,0.972973,0.982143,0.956522,0.982143,0.964912] f_measure 0.9787801275770488 [1,0.974359,0.990826,0.973913,0.990991,0.972477,1,0.990991,0.946429,0.948276] f_measure 0.9804665128147689 [0.982143,0.957265,1,0.982456,0.982456,0.982143,0.981818,1,0.972477,0.964286] kappa 0.9762748236618529 kappa 0.9802289501642896 kappa 0.986160070360598 kappa 0.9782520747070432 kappa 0.9782514626260779 kappa 0.9683649847665018 kappa 0.9802290892716424 kappa 0.9703440512207134 kappa 0.9762744063324538 kappa 0.9782519216900318 kb_relative_information_score 0.9731964415804311 kb_relative_information_score 0.981312141060449 kb_relative_information_score 0.9810167672132343 kb_relative_information_score 0.9759972514579246 kb_relative_information_score 0.9772264545714975 kb_relative_information_score 0.9649141657101571 kb_relative_information_score 0.9779576303628525 kb_relative_information_score 0.9707967694286785 kb_relative_information_score 0.970419205362371 kb_relative_information_score 0.977827154670136 mean_absolute_error 0.007258409757853911 mean_absolute_error 0.0057166761962944655 mean_absolute_error 0.005970962293469847 mean_absolute_error 0.007037210199498038 mean_absolute_error 0.006053742526168216 mean_absolute_error 0.009345637721918964 mean_absolute_error 0.006392710444380732 mean_absolute_error 0.007779764756010059 mean_absolute_error 0.007904685884340887 mean_absolute_error 0.006018533565840004 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 0.978828172530984 [1,0.965517,0.982143,0.982759,0.981818,1,0.964912,0.982143,0.947368,0.981481] precision 0.9825079737933325 [1,1,1,0.982456,0.965517,0.949153,1,1,0.981818,0.946429] precision 0.9877571543560507 [1,0.982759,1,0.965517,0.982456,1,1,0.966102,0.981818,1] precision 0.9808834883607416 [1,0.949153,1,0.981818,1,1,0.982456,1,0.964286,0.931034] precision 0.9808051992106606 [1,0.966102,1,0.982759,0.95,0.981818,1,0.982759,0.964286,0.981132] precision 0.9725900443593253 [0.981818,0.95,1,1,0.932203,1,1,0.982143,0.963636,0.918033] precision 0.9824819354777019 [1,0.982759,0.982143,1,1,0.948276,0.981818,0.965517,0.982143,0.981818] precision 0.9735470463569165 [0.982456,0.982143,0.981818,0.981481,0.982143,0.981818,0.964912,0.948276,0.982143,0.948276] precision 0.9793624811335209 [1,0.966102,1,0.965517,1,1,1,1,0.946429,0.916667] precision 0.9809056325929563 [0.982143,0.933333,1,0.982456,0.965517,0.982143,1,1,1,0.964286] predictive_accuracy 0.9786476868327402 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9804270462633453 predictive_accuracy 0.9804270462633453 predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9786476868327402 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 0.04032522085844691 relative_absolute_error 0.031759881004563194 relative_absolute_error 0.03317253694990458 relative_absolute_error 0.039096230036890105 relative_absolute_error 0.033632481642200666 relative_absolute_error 0.05192110298024983 relative_absolute_error 0.035515531954883064 relative_absolute_error 0.04322149207249351 relative_absolute_error 0.04391543049304591 relative_absolute_error 0.03343652068177924 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 0.06012328650533868 root_mean_squared_error 0.047457532981345626 root_mean_squared_error 0.04548326718018122 root_mean_squared_error 0.05434625087905793 root_mean_squared_error 0.054289488699529376 root_mean_squared_error 0.0695363194404005 root_mean_squared_error 0.05090874700267288 root_mean_squared_error 0.06149623564289282 root_mean_squared_error 0.06284451154426508 root_mean_squared_error 0.05295147410671372 root_relative_squared_error 0.20041307602877317 root_relative_squared_error 0.15819345079687033 root_relative_squared_error 0.151612175692534 root_relative_squared_error 0.1811557051050314 root_relative_squared_error 0.18096675043832228 root_relative_squared_error 0.2317900217520284 root_relative_squared_error 0.1696968445773976 root_relative_squared_error 0.20498868576433615 root_relative_squared_error 0.20948259799527094 root_relative_squared_error 0.17650479822322712 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 0.9787258506768488 [1,0.982456,0.982143,0.982759,0.947368,1,0.982143,0.982143,0.981818,0.946429] unweighted_recall 0.9822961989613532 [1,0.982456,1,0.965517,0.982456,1,1,0.964286,0.981818,0.946429] unweighted_recall 0.9875301891091365 [1,1,0.982143,0.982456,0.982456,1,1,1,0.981818,0.946429] unweighted_recall 0.9805126452494873 [1,0.982456,0.964286,0.947368,1,1,1,0.964912,0.981818,0.964286] unweighted_recall 0.9804163818637501 [0.981818,1,1,1,1,0.981818,0.946429,1,0.981818,0.912281] unweighted_recall 0.9714205969469125 [0.981818,1,0.982143,0.964912,0.964912,0.927273,0.982143,0.964912,0.963636,0.982456] unweighted_recall 0.9822357028935975 [0.982143,1,1,0.947368,1,0.982143,0.981818,0.982456,0.982143,0.964286] unweighted_recall 0.9734951013898383 [1,0.964912,0.981818,0.929825,0.964912,0.964286,1,0.964912,0.982143,0.982143] unweighted_recall 0.9786318657144429 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.946429,0.982143] unweighted_recall 0.9804197994987467 [0.982143,0.982456,1,0.982456,1,0.982143,0.964286,1,0.946429,0.964286] usercpu_time_millis 16512.834606999604 usercpu_time_millis 16669.745206001608 usercpu_time_millis 16585.156608000034 usercpu_time_millis 16499.611006998748 usercpu_time_millis 16650.906307000696 usercpu_time_millis 16611.32820399871 usercpu_time_millis 16609.313601000395 usercpu_time_millis 16515.580603998387 usercpu_time_millis 16435.39989999954 usercpu_time_millis 16617.204506001144 usercpu_time_millis_testing 9.514100000160397 usercpu_time_millis_testing 8.971100000053411 usercpu_time_millis_testing 8.825099999739905 usercpu_time_millis_testing 10.102499998538406 usercpu_time_millis_testing 8.329500000400003 usercpu_time_millis_testing 9.290199999668403 usercpu_time_millis_testing 8.993400000690599 usercpu_time_millis_testing 9.967399999368354 usercpu_time_millis_testing 11.719199999788543 usercpu_time_millis_testing 10.081300000820193 usercpu_time_millis_training 16503.320506999444 usercpu_time_millis_training 16660.774106001554 usercpu_time_millis_training 16576.331508000294 usercpu_time_millis_training 16489.50850700021 usercpu_time_millis_training 16642.576807000296 usercpu_time_millis_training 16602.03800399904 usercpu_time_millis_training 16600.320200999704 usercpu_time_millis_training 16505.61320399902 usercpu_time_millis_training 16423.68069999975 usercpu_time_millis_training 16607.123206000324 wall_clock_time_millis 16513.645887374878 wall_clock_time_millis 16682.069778442383 wall_clock_time_millis 16610.095977783203 wall_clock_time_millis 16527.763843536377 wall_clock_time_millis 16713.73748779297 wall_clock_time_millis 16639.43338394165 wall_clock_time_millis 16626.285314559937 wall_clock_time_millis 16585.77036857605 wall_clock_time_millis 16451.99179649353 wall_clock_time_millis 16652.392148971558 wall_clock_time_millis_testing 9.521961212158203 wall_clock_time_millis_testing 8.974075317382812 wall_clock_time_millis_testing 8.829116821289062 wall_clock_time_millis_testing 10.113000869750977 wall_clock_time_millis_testing 8.332490921020508 wall_clock_time_millis_testing 9.293317794799805 wall_clock_time_millis_testing 8.999109268188477 wall_clock_time_millis_testing 9.969949722290039 wall_clock_time_millis_testing 11.725187301635742 wall_clock_time_millis_testing 10.087251663208008 wall_clock_time_millis_training 16504.12392616272 wall_clock_time_millis_training 16673.095703125 wall_clock_time_millis_training 16601.266860961914 wall_clock_time_millis_training 16517.650842666626 wall_clock_time_millis_training 16705.40499687195 wall_clock_time_millis_training 16630.14006614685 wall_clock_time_millis_training 16617.286205291748 wall_clock_time_millis_training 16575.80041885376 wall_clock_time_millis_training 16440.266609191895 wall_clock_time_millis_training 16642.30489730835 weighted_recall 0.9786476868327402 [1,0.982456,0.982143,0.982759,0.947368,1,0.982143,0.982143,0.981818,0.946429] weighted_recall 0.9822064056939501 [1,0.982456,1,0.965517,0.982456,1,1,0.964286,0.981818,0.946429] weighted_recall 0.9875444839857651 [1,1,0.982143,0.982456,0.982456,1,1,1,0.981818,0.946429] weighted_recall 0.9804270462633452 [1,0.982456,0.964286,0.947368,1,1,1,0.964912,0.981818,0.964286] weighted_recall 0.9804270462633452 [0.981818,1,1,1,1,0.981818,0.946429,1,0.981818,0.912281] weighted_recall 0.9715302491103203 [0.981818,1,0.982143,0.964912,0.964912,0.927273,0.982143,0.964912,0.963636,0.982456] weighted_recall 0.9822064056939501 [0.982143,1,1,0.947368,1,0.982143,0.981818,0.982456,0.982143,0.964286] weighted_recall 0.9733096085409253 [1,0.964912,0.981818,0.929825,0.964912,0.964286,1,0.964912,0.982143,0.982143] weighted_recall 0.9786476868327402 [1,0.982759,0.981818,0.982456,0.982143,0.946429,1,0.982143,0.946429,0.982143] weighted_recall 0.9804270462633452 [0.982143,0.982456,1,0.982456,1,0.982143,0.964286,1,0.946429,0.964286]