10590770 32117 VAIBHAV JAISWAL 37 Supervised Classification 19161 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.neighbors._classification.KNeighborsClassifier)(1) 8304079 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 algorithm "auto" 19154 leaf_size 30 19154 metric "minkowski" 19154 metric_params null 19154 n_jobs null 19154 n_neighbors 5 19154 p 2 19154 weights "uniform" 19154 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 19161 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"}}] 19161 verbose false 19161 openml-python Sklearn_1.0.2. 37 diabetes https://www.openml.org/data/download/37/dataset_37_diabetes.arff -1 22109136 description https://api.openml.org/data/download/22109136/description.xml -1 22109137 predictions https://api.openml.org/data/download/22109137/predictions.arff area_under_roc_curve 0.7767761194029851 [0.776776,0.776776] average_cost 0 f_measure 0.7370703913921582 [0.809249,0.60241] kappa 0.41329711710599415 kb_relative_information_score 0.29979491757787846 mean_absolute_error 0.31614583333333285 mean_prior_absolute_error 0.4544913419913401 weighted_recall 0.7421875 [0.84,0.559701] number_of_instances 768 [500,268] precision 0.735829663003071 [0.780669,0.652174] predictive_accuracy 0.7421875 prior_entropy 0.9331348051619819 relative_absolute_error 0.6956036432908698 root_mean_prior_squared_error 0.4766409223329586 root_mean_squared_error 0.4289036410819257 root_relative_squared_error 0.8998464483129589 total_cost 0 unweighted_recall 0.6998507462686567 [0.84,0.559701] area_under_roc_curve 0.8818518518518519 [0.881852,0.881852] area_under_roc_curve 0.6688888888888889 [0.668889,0.668889] area_under_roc_curve 0.8288888888888888 [0.828889,0.828889] area_under_roc_curve 0.762962962962963 [0.762963,0.762963] area_under_roc_curve 0.7359259259259259 [0.735926,0.735926] area_under_roc_curve 0.7377777777777778 [0.737778,0.737778] area_under_roc_curve 0.8185185185185185 [0.818519,0.818519] area_under_roc_curve 0.7755555555555557 [0.775556,0.775556] area_under_roc_curve 0.7530769230769231 [0.753077,0.753077] area_under_roc_curve 0.7826923076923077 [0.782692,0.782692] 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 0.8043214024906533 [0.851485,0.716981] f_measure 0.6670602125147579 [0.781818,0.454545] f_measure 0.7640300875594993 [0.823529,0.653846] f_measure 0.7045148247978437 [0.792453,0.541667] f_measure 0.7198515769944341 [0.8,0.571429] f_measure 0.6531558512025142 [0.721649,0.526316] f_measure 0.7582394021073267 [0.830189,0.625] f_measure 0.7387584892172047 [0.825688,0.577778] f_measure 0.7697435077054338 [0.838095,0.638298] f_measure 0.7789572337591871 [0.824742,0.690909] kappa 0.5685468808367576 kappa 0.25182186234817816 kappa 0.4777694046721929 kappa 0.33879781420765026 kappa 0.3744680851063831 kappa 0.24918743228602383 kappa 0.459016393442623 kappa 0.4131568391496189 kappa 0.47903225806451605 kappa 0.5164670658682634 kb_relative_information_score 0.44238823847581804 kb_relative_information_score 0.19014070273683867 kb_relative_information_score 0.3665309887126845 kb_relative_information_score 0.2689008067407496 kb_relative_information_score 0.23997595158358428 kb_relative_information_score 0.20998549646934378 kb_relative_information_score 0.35479277745255267 kb_relative_information_score 0.31237717265319076 kb_relative_information_score 0.27296346790669895 kb_relative_information_score 0.3401792994684248 mean_absolute_error 0.25454545454545446 mean_absolute_error 0.3610389610389608 mean_absolute_error 0.2883116883116882 mean_absolute_error 0.3298701298701297 mean_absolute_error 0.34285714285714264 mean_absolute_error 0.3480519480519481 mean_absolute_error 0.2935064935064934 mean_absolute_error 0.31688311688311666 mean_absolute_error 0.3289473684210524 mean_absolute_error 0.29736842105263156 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.4550008433125322 mean_prior_absolute_error 0.45242652084757423 mean_prior_absolute_error 0.45242652084757423 number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 77 [50,27] number_of_instances 76 [50,26] number_of_instances 76 [50,26] precision 0.8037354802060683 [0.843137,0.730769] precision 0.6716322892793481 [0.716667,0.588235] precision 0.7629170829170829 [0.807692,0.68] precision 0.7040816326530612 [0.75,0.619048] precision 0.71900826446281 [0.763636,0.636364] precision 0.6588836695219673 [0.744681,0.5] precision 0.7606679035250463 [0.785714,0.714286] precision 0.74851419766674 [0.762712,0.722222] precision 0.7706766917293233 [0.8,0.714286] precision 0.7840483453681893 [0.851064,0.655172] predictive_accuracy 0.8051948051948052 predictive_accuracy 0.6883116883116882 predictive_accuracy 0.7662337662337663 predictive_accuracy 0.7142857142857143 predictive_accuracy 0.7272727272727273 predictive_accuracy 0.6493506493506493 predictive_accuracy 0.7662337662337663 predictive_accuracy 0.7532467532467533 predictive_accuracy 0.7763157894736843 predictive_accuracy 0.7763157894736843 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9346519933901933 prior_entropy 0.9269862002370954 prior_entropy 0.9269862002370954 relative_absolute_error 0.5594395225562507 relative_absolute_error 0.7934907513808044 relative_absolute_error 0.6336508877933043 relative_absolute_error 0.7249879527004471 relative_absolute_error 0.7535307854839293 relative_absolute_error 0.7649479185973227 relative_absolute_error 0.6450680209066972 relative_absolute_error 0.6964451199169649 relative_absolute_error 0.7270735760688909 relative_absolute_error 0.6572745127662778 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4771750938215478 root_mean_prior_squared_error 0.4744699650121647 root_mean_prior_squared_error 0.4744699650121647 root_mean_squared_error 0.3632465443029734 root_mean_squared_error 0.4775478489658894 root_mean_squared_error 0.3980471811752451 root_mean_squared_error 0.444884342185784 root_mean_squared_error 0.4454677973114985 root_mean_squared_error 0.44779401572540073 root_mean_squared_error 0.41840761831608053 root_mean_squared_error 0.4239578513723499 root_mean_squared_error 0.4358898943540672 root_mean_squared_error 0.4236433455284365 root_relative_squared_error 0.7612437216574822 root_relative_squared_error 1.000781170579035 root_relative_squared_error 0.8341742608303554 root_relative_squared_error 0.9323293439790471 root_relative_squared_error 0.9335520715129632 root_relative_squared_error 0.9384270502032218 root_relative_squared_error 0.8768429528984493 root_relative_squared_error 0.8884743920245346 root_relative_squared_error 0.9186880656247476 root_relative_squared_error 0.8928770560167595 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 0.7818518518518518 [0.86,0.703704] unweighted_recall 0.6151851851851852 [0.86,0.37037] unweighted_recall 0.7348148148148148 [0.84,0.62963] unweighted_recall 0.6607407407407407 [0.84,0.481481] unweighted_recall 0.6792592592592592 [0.84,0.518519] unweighted_recall 0.6277777777777778 [0.7,0.555556] unweighted_recall 0.7177777777777778 [0.88,0.555556] unweighted_recall 0.6907407407407408 [0.9,0.481481] unweighted_recall 0.7284615384615385 [0.88,0.576923] unweighted_recall 0.7653846153846153 [0.8,0.730769] usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 usercpu_time_millis 15.625 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 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_training 15.625 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 0 usercpu_time_millis_training 15.625 usercpu_time_millis_training 0 usercpu_time_millis_training 0 usercpu_time_millis_training 0 wall_clock_time_millis 13.010263442993164 wall_clock_time_millis 12.970447540283203 wall_clock_time_millis 16.008615493774414 wall_clock_time_millis 15.990495681762695 wall_clock_time_millis 13.972282409667969 wall_clock_time_millis 13.988733291625977 wall_clock_time_millis 14.989137649536133 wall_clock_time_millis 14.98723030090332 wall_clock_time_millis 12.99595832824707 wall_clock_time_millis 13.01264762878418 wall_clock_time_millis_testing 6.014823913574219 wall_clock_time_millis_testing 6.996393203735352 wall_clock_time_millis_testing 6.994724273681641 wall_clock_time_millis_testing 6.973505020141602 wall_clock_time_millis_testing 6.977558135986328 wall_clock_time_millis_testing 6.974935531616211 wall_clock_time_millis_testing 7.017612457275391 wall_clock_time_millis_testing 5.9967041015625 wall_clock_time_millis_testing 6.976604461669922 wall_clock_time_millis_testing 5.995988845825195 wall_clock_time_millis_training 6.995439529418945 wall_clock_time_millis_training 5.974054336547852 wall_clock_time_millis_training 9.013891220092773 wall_clock_time_millis_training 9.016990661621094 wall_clock_time_millis_training 6.994724273681641 wall_clock_time_millis_training 7.013797760009766 wall_clock_time_millis_training 7.971525192260742 wall_clock_time_millis_training 8.99052619934082 wall_clock_time_millis_training 6.019353866577148 wall_clock_time_millis_training 7.016658782958984 weighted_recall 0.8051948051948052 [0.86,0.703704] weighted_recall 0.6883116883116883 [0.86,0.37037] weighted_recall 0.7662337662337663 [0.84,0.62963] weighted_recall 0.7142857142857143 [0.84,0.481481] weighted_recall 0.7272727272727273 [0.84,0.518519] weighted_recall 0.6493506493506493 [0.7,0.555556] weighted_recall 0.7662337662337663 [0.88,0.555556] weighted_recall 0.7532467532467533 [0.9,0.481481] weighted_recall 0.7763157894736842 [0.88,0.576923] weighted_recall 0.7763157894736842 [0.8,0.730769]