10591035 32117 VAIBHAV JAISWAL 10101 Supervised Classification 19162 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.tree._classes.DecisionTreeClassifier)(1) 8304396 Python_3.7.7. Sklearn_1.0.2. NumPy_1.21.6. SciPy_1.7.3. copy true 19075 with_mean true 19075 with_std true 19075 add_indicator false 19084 copy true 19084 fill_value null 19084 missing_values NaN 19084 strategy "mean" 19084 verbose 0 19084 ccp_alpha 0.0 19085 class_weight null 19085 criterion "gini" 19085 max_depth null 19085 max_features null 19085 max_leaf_nodes null 19085 min_impurity_decrease 0.0 19085 min_samples_leaf 1 19085 min_samples_split 2 19085 min_weight_fraction_leaf 0.0 19085 random_state 47361 19085 splitter "best" 19085 memory null 19156 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "scaler", "step_name": "scaler"}}] 19156 verbose false 19156 memory null 19162 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "numerical", "step_name": "numerical"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "model", "step_name": "model"}}] 19162 verbose false 19162 openml-python Sklearn_1.0.2. 1464 blood-transfusion-service-center https://www.openml.org/data/download/1586225/php0iVrYT -1 22109666 description https://api.openml.org/data/download/22109666/description.xml -1 22109667 predictions https://api.openml.org/data/download/22109667/predictions.arff area_under_roc_curve 0.6016164005519417 [0.601616,0.601616] average_cost 0 f_measure 0.7074724504273251 [0.820119,0.346749] kappa 0.16925635843018347 kb_relative_information_score 0.07565846298434355 mean_absolute_error 0.30244322156413145 mean_prior_absolute_error 0.3630445632798566 weighted_recall 0.7179144385026738 [0.84386,0.314607] number_of_instances 748 [570,178] precision 0.6997612894406816 [0.797678,0.386207] predictive_accuracy 0.7179144385026739 prior_entropy 0.7916465694609683 relative_absolute_error 0.8330746474531006 root_mean_prior_squared_error 0.4258399633559147 root_mean_squared_error 0.5149108264558916 root_relative_squared_error 1.2091651107567187 total_cost 0 unweighted_recall 0.5792331953479204 [0.84386,0.314607] area_under_roc_curve 0.5399610136452242 [0.539961,0.539961] area_under_roc_curve 0.5745614035087719 [0.574561,0.574561] area_under_roc_curve 0.6038011695906433 [0.603801,0.603801] area_under_roc_curve 0.6549707602339181 [0.654971,0.654971] area_under_roc_curve 0.6798245614035088 [0.679825,0.679825] area_under_roc_curve 0.5974658869395711 [0.597466,0.597466] area_under_roc_curve 0.5960038986354775 [0.596004,0.596004] area_under_roc_curve 0.5653021442495126 [0.565302,0.565302] area_under_roc_curve 0.6986584107327142 [0.698658,0.698658] area_under_roc_curve 0.5294117647058822 [0.529412,0.529412] 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 0.6364223602484471 [0.765217,0.228571] f_measure 0.7137127371273713 [0.845528,0.296296] f_measure 0.6750447275684467 [0.806723,0.258065] f_measure 0.7441490683229813 [0.834783,0.457143] f_measure 0.8048305084745763 [0.881356,0.5625] f_measure 0.6654237288135593 [0.79661,0.25] f_measure 0.7211864406779661 [0.830508,0.375] f_measure 0.7108624708624709 [0.820513,0.363636] f_measure 0.7567567567567568 [0.842105,0.470588] f_measure 0.6406978098788444 [0.775862,0.1875] kappa -0.005961251862891171 kappa 0.16225749559082905 kappa 0.07108239095315017 kappa 0.29210134128166926 kappa 0.4462025316455696 kappa 0.05063291139240509 kappa 0.20886075949367064 kappa 0.18604651162790684 kappa 0.3126934984520125 kappa -0.03552206673842816 kb_relative_information_score -0.1536747487596714 kb_relative_information_score 0.18559942615805458 kb_relative_information_score 0.030315152196524465 kb_relative_information_score 0.16008703538777275 kb_relative_information_score 0.29697463015965486 kb_relative_information_score 0.012351265638081066 kb_relative_information_score 0.09483793828074268 kb_relative_information_score 0.04718791985022002 kb_relative_information_score 0.206811415963828 kb_relative_information_score -0.1263619141614493 mean_absolute_error 0.37491882447054853 mean_absolute_error 0.27308702408702396 mean_absolute_error 0.3213492063492063 mean_absolute_error 0.2812115483083224 mean_absolute_error 0.23257142857142862 mean_absolute_error 0.3206349206349207 mean_absolute_error 0.2917261904761904 mean_absolute_error 0.3161898025346302 mean_absolute_error 0.2549990450725744 mean_absolute_error 0.35785039847539846 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.35873873873873896 mean_prior_absolute_error 0.35873873873873896 number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 74 [57,17] number_of_instances 74 [57,17] precision 0.6330223123732251 [0.758621,0.235294] precision 0.7054545454545454 [0.787879,0.444444] precision 0.6622332506203473 [0.774194,0.307692] precision 0.7419066937119675 [0.827586,0.470588] precision 0.8021545667447306 [0.852459,0.642857] precision 0.6541451990632319 [0.770492,0.285714] precision 0.7133489461358313 [0.803279,0.428571] precision 0.7040000000000001 [0.8,0.4] precision 0.7567567567567568 [0.842105,0.470588] precision 0.6334402198808977 [0.762712,0.2] predictive_accuracy 0.64 predictive_accuracy 0.7466666666666667 predictive_accuracy 0.6933333333333332 predictive_accuracy 0.7466666666666667 predictive_accuracy 0.8133333333333332 predictive_accuracy 0.68 predictive_accuracy 0.7333333333333333 predictive_accuracy 0.72 predictive_accuracy 0.7567567567567568 predictive_accuracy 0.6486486486486487 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7778597106646706 prior_entropy 0.7778597106646706 relative_absolute_error 1.0296950283906228 relative_absolute_error 0.750019291289248 relative_absolute_error 0.8825688617324761 relative_absolute_error 0.772332873997516 relative_absolute_error 0.6387453179601998 relative_absolute_error 0.8806071132129428 relative_absolute_error 0.8012107911862556 relative_absolute_error 0.8683988278195859 relative_absolute_error 0.7108210447778941 relative_absolute_error 0.9975237124753694 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4207539065176338 root_mean_prior_squared_error 0.4207539065176338 root_mean_squared_error 0.586311660874269 root_mean_squared_error 0.48333718988926244 root_mean_squared_error 0.5229725094627986 root_mean_squared_error 0.48894955809790663 root_mean_squared_error 0.43914367299652607 root_mean_squared_error 0.5245126893045486 root_mean_squared_error 0.5179053260353756 root_mean_squared_error 0.516209888147743 root_mean_squared_error 0.47668841773673304 root_mean_squared_error 0.5760875706263181 root_relative_squared_error 1.372821266703529 root_relative_squared_error 1.1317113705009403 root_relative_squared_error 1.2245156131148518 root_relative_squared_error 1.1448524675446332 root_relative_squared_error 1.0282343225597421 root_relative_squared_error 1.2281218720082017 root_relative_squared_error 1.212651040677249 root_relative_squared_error 1.2086812523482122 root_relative_squared_error 1.1329387804905742 root_relative_squared_error 1.3691793746950613 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 0.49707602339181284 [0.77193,0.222222] unweighted_recall 0.567251461988304 [0.912281,0.222222] unweighted_recall 0.5321637426900585 [0.842105,0.222222] unweighted_recall 0.6432748538011696 [0.842105,0.444444] unweighted_recall 0.706140350877193 [0.912281,0.5] unweighted_recall 0.5233918128654971 [0.824561,0.222222] unweighted_recall 0.5964912280701754 [0.859649,0.333333] unweighted_recall 0.587719298245614 [0.842105,0.333333] unweighted_recall 0.6563467492260062 [0.842105,0.470588] unweighted_recall 0.48297213622291024 [0.789474,0.176471] usercpu_time_millis 0 usercpu_time_millis 0 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 0 usercpu_time_millis 0 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 15.625 usercpu_time_millis_training 0 usercpu_time_millis_training 0 usercpu_time_millis_training 15.625 usercpu_time_millis_training 0 usercpu_time_millis_training 0 usercpu_time_millis_training 0 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 usercpu_time_millis_training 0 wall_clock_time_millis 8.99505615234375 wall_clock_time_millis 10.01596450805664 wall_clock_time_millis 9.97304916381836 wall_clock_time_millis 9.992837905883789 wall_clock_time_millis 9.973764419555664 wall_clock_time_millis 11.014938354492188 wall_clock_time_millis 12.972831726074219 wall_clock_time_millis 9.994268417358398 wall_clock_time_millis 10.974884033203125 wall_clock_time_millis 10.994195938110352 wall_clock_time_millis_testing 2.9990673065185547 wall_clock_time_millis_testing 1.9993782043457031 wall_clock_time_millis_testing 1.9974708557128906 wall_clock_time_millis_testing 2.998828887939453 wall_clock_time_millis_testing 2.0008087158203125 wall_clock_time_millis_testing 1.9977092742919922 wall_clock_time_millis_testing 1.9996166229248047 wall_clock_time_millis_testing 1.9998550415039062 wall_clock_time_millis_testing 1.9996166229248047 wall_clock_time_millis_testing 3.9975643157958984 wall_clock_time_millis_training 5.995988845825195 wall_clock_time_millis_training 8.016586303710938 wall_clock_time_millis_training 7.975578308105469 wall_clock_time_millis_training 6.994009017944336 wall_clock_time_millis_training 7.972955703735352 wall_clock_time_millis_training 9.017229080200195 wall_clock_time_millis_training 10.973215103149414 wall_clock_time_millis_training 7.994413375854492 wall_clock_time_millis_training 8.97526741027832 wall_clock_time_millis_training 6.996631622314453 weighted_recall 0.64 [0.77193,0.222222] weighted_recall 0.7466666666666667 [0.912281,0.222222] weighted_recall 0.6933333333333334 [0.842105,0.222222] weighted_recall 0.7466666666666667 [0.842105,0.444444] weighted_recall 0.8133333333333334 [0.912281,0.5] weighted_recall 0.68 [0.824561,0.222222] weighted_recall 0.7333333333333333 [0.859649,0.333333] weighted_recall 0.72 [0.842105,0.333333] weighted_recall 0.7567567567567568 [0.842105,0.470588] weighted_recall 0.6486486486486487 [0.789474,0.176471]