10591519 32117 VAIBHAV JAISWAL 10101 Supervised Classification 19165 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.svm._classes.SVC)(1) 8304104 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 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 19165 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"}}] 19165 verbose false 19165 C 1.0 19166 break_ties false 19166 cache_size 200 19166 class_weight null 19166 coef0 0.0 19166 decision_function_shape "ovr" 19166 degree 3 19166 gamma "scale" 19166 kernel "rbf" 19166 max_iter -1 19166 probability false 19166 random_state 0 19166 shrinking true 19166 tol 0.001 19166 verbose false 19166 openml-python Sklearn_1.0.2. 1464 blood-transfusion-service-center https://www.openml.org/data/download/1586225/php0iVrYT -1 22110644 description https://api.openml.org/data/download/22110644/description.xml -1 22110645 predictions https://api.openml.org/data/download/22110645/predictions.arff area_under_roc_curve 0.5723437808003154 [0.572344,0.572344] average_cost 0 f_measure 0.7283303453071093 [0.868878,0.278261] kappa 0.1912354749622219 kb_relative_information_score 0.310286590409157 mean_absolute_error 0.22192513368983957 mean_prior_absolute_error 0.3630445632798566 weighted_recall 0.7780748663101604 [0.964912,0.179775] number_of_instances 748 [570,178] precision 0.7486223208839842 [0.79023,0.615385] predictive_accuracy 0.7780748663101604 prior_entropy 0.7916465694609683 relative_absolute_error 0.6112889604650719 root_mean_prior_squared_error 0.4258399633559147 root_mean_squared_error 0.471089305429278 root_relative_squared_error 1.1062590314839573 total_cost 0 unweighted_recall 0.5723437808003153 [0.964912,0.179775] area_under_roc_curve 0.5116959064327485 [0.511696,0.511696] area_under_roc_curve 0.6111111111111112 [0.611111,0.611111] area_under_roc_curve 0.49269005847953223 [0.49269,0.49269] area_under_roc_curve 0.5102339181286549 [0.510234,0.510234] area_under_roc_curve 0.621345029239766 [0.621345,0.621345] area_under_roc_curve 0.5555555555555556 [0.555556,0.555556] area_under_roc_curve 0.6111111111111112 [0.611111,0.611111] area_under_roc_curve 0.621345029239766 [0.621345,0.621345] area_under_roc_curve 0.6589267285861713 [0.658927,0.658927] area_under_roc_curve 0.5325077399380806 [0.532508,0.532508] 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 0.67072 [0.832,0.16] f_measure 0.7641477272727273 [0.890625,0.363636] f_measure 0.6552002738788086 [0.834646,0.086957] f_measure 0.6709191583610189 [0.852713,0.095238] f_measure 0.7648 [0.88,0.4] f_measure 0.7144615384615385 [0.876923,0.2] f_measure 0.7641477272727273 [0.890625,0.363636] f_measure 0.7648 [0.88,0.4] f_measure 0.799129861568886 [0.894309,0.48] f_measure 0.702000702000702 [0.857143,0.181818] kappa 0.02957486136783716 kappa 0.3027888446215141 kappa -0.01941747572815563 kappa 0.028629856850715996 kappa 0.3068391866913125 kappa 0.1596638655462184 kappa 0.3027888446215141 kappa 0.3068391866913125 kappa 0.3903675538656527 kappa 0.08641975308642007 kb_relative_information_score 0.13351996032345792 kb_relative_information_score 0.422346640215639 kb_relative_information_score 0.1335199603234579 kb_relative_information_score 0.21604186886408108 kb_relative_information_score 0.3810856859453275 kb_relative_information_score 0.3398247316750158 kb_relative_information_score 0.422346640215639 kb_relative_information_score 0.3810856859453275 kb_relative_information_score 0.44434673763984356 kb_relative_information_score 0.2306339444243981 mean_absolute_error 0.28 mean_absolute_error 0.18666666666666668 mean_absolute_error 0.28 mean_absolute_error 0.25333333333333335 mean_absolute_error 0.2 mean_absolute_error 0.21333333333333335 mean_absolute_error 0.18666666666666668 mean_absolute_error 0.2 mean_absolute_error 0.17567567567567569 mean_absolute_error 0.24324324324324326 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 0.6497478991596639 [0.764706,0.285714] precision 0.8501408450704226 [0.802817,1] precision 0.6234285714285714 [0.757143,0.2] precision 0.6605555555555556 [0.763889,0.333333] precision 0.7861344537815126 [0.808824,0.714286] precision 0.8334246575342465 [0.780822,1] precision 0.8501408450704226 [0.802817,1] precision 0.7861344537815126 [0.808824,0.714286] precision 0.8141891891891891 [0.833333,0.75] precision 0.6947121034077557 [0.782609,0.4] predictive_accuracy 0.72 predictive_accuracy 0.8133333333333332 predictive_accuracy 0.72 predictive_accuracy 0.7466666666666667 predictive_accuracy 0.8 predictive_accuracy 0.7866666666666667 predictive_accuracy 0.8133333333333332 predictive_accuracy 0.8 predictive_accuracy 0.8243243243243243 predictive_accuracy 0.7567567567567568 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 0.769005419657243 relative_absolute_error 0.5126702797714953 relative_absolute_error 0.769005419657243 relative_absolute_error 0.6957668082613151 relative_absolute_error 0.5492895854694592 relative_absolute_error 0.5859088911674233 relative_absolute_error 0.5126702797714953 relative_absolute_error 0.5492895854694592 relative_absolute_error 0.48970366649924635 relative_absolute_error 0.678051230537418 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 0.5291502622129182 root_mean_squared_error 0.43204937989385733 root_mean_squared_error 0.5291502622129182 root_mean_squared_error 0.5033222956847166 root_mean_squared_error 0.4472135954999579 root_mean_squared_error 0.46188021535170065 root_mean_squared_error 0.43204937989385733 root_mean_squared_error 0.4472135954999579 root_mean_squared_error 0.4191368221424547 root_mean_squared_error 0.4931969619160719 root_relative_squared_error 1.2389805315562727 root_relative_squared_error 1.011623367851713 root_relative_squared_error 1.2389805315562727 root_relative_squared_error 1.1785055587870965 root_relative_squared_error 1.0471296677705828 root_relative_squared_error 1.0814708705587128 root_relative_squared_error 1.011623367851713 root_relative_squared_error 1.0471296677705828 root_relative_squared_error 0.9961566978936384 root_relative_squared_error 1.1721744094974955 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 0.5116959064327485 [0.912281,0.111111] unweighted_recall 0.6111111111111112 [1,0.222222] unweighted_recall 0.4926900584795322 [0.929825,0.055556] unweighted_recall 0.5102339181286549 [0.964912,0.055556] unweighted_recall 0.6213450292397661 [0.964912,0.277778] unweighted_recall 0.5555555555555556 [1,0.111111] unweighted_recall 0.6111111111111112 [1,0.222222] unweighted_recall 0.6213450292397661 [0.964912,0.277778] unweighted_recall 0.6589267285861713 [0.964912,0.352941] unweighted_recall 0.5325077399380804 [0.947368,0.117647] usercpu_time_millis 31.25 usercpu_time_millis 15.625 usercpu_time_millis 31.25 usercpu_time_millis 46.875 usercpu_time_millis 31.25 usercpu_time_millis 31.25 usercpu_time_millis 31.25 usercpu_time_millis 31.25 usercpu_time_millis 15.625 usercpu_time_millis 31.25 usercpu_time_millis_testing 15.625 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 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_training 15.625 usercpu_time_millis_training 15.625 usercpu_time_millis_training 31.25 usercpu_time_millis_training 31.25 usercpu_time_millis_training 31.25 usercpu_time_millis_training 15.625 usercpu_time_millis_training 31.25 usercpu_time_millis_training 31.25 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 wall_clock_time_millis 26.98493003845215 wall_clock_time_millis 25.983095169067383 wall_clock_time_millis 27.980566024780273 wall_clock_time_millis 37.976741790771484 wall_clock_time_millis 39.97492790222168 wall_clock_time_millis 27.982711791992188 wall_clock_time_millis 26.00693702697754 wall_clock_time_millis 29.980897903442383 wall_clock_time_millis 24.983644485473633 wall_clock_time_millis 26.980161666870117 wall_clock_time_millis_testing 5.998134613037109 wall_clock_time_millis_testing 5.01561164855957 wall_clock_time_millis_testing 5.997657775878906 wall_clock_time_millis_testing 12.980461120605469 wall_clock_time_millis_testing 5.995512008666992 wall_clock_time_millis_testing 5.996465682983398 wall_clock_time_millis_testing 5.015850067138672 wall_clock_time_millis_testing 6.018877029418945 wall_clock_time_millis_testing 4.997014999389648 wall_clock_time_millis_testing 6.974220275878906 wall_clock_time_millis_training 20.98679542541504 wall_clock_time_millis_training 20.967483520507812 wall_clock_time_millis_training 21.982908248901367 wall_clock_time_millis_training 24.996280670166016 wall_clock_time_millis_training 33.97941589355469 wall_clock_time_millis_training 21.98624610900879 wall_clock_time_millis_training 20.991086959838867 wall_clock_time_millis_training 23.962020874023438 wall_clock_time_millis_training 19.986629486083984 wall_clock_time_millis_training 20.00594139099121 weighted_recall 0.72 [0.912281,0.111111] weighted_recall 0.8133333333333334 [1,0.222222] weighted_recall 0.72 [0.929825,0.055556] weighted_recall 0.7466666666666667 [0.964912,0.055556] weighted_recall 0.8 [0.964912,0.277778] weighted_recall 0.7866666666666666 [1,0.111111] weighted_recall 0.8133333333333334 [1,0.222222] weighted_recall 0.8 [0.964912,0.277778] weighted_recall 0.8243243243243243 [0.964912,0.352941] weighted_recall 0.7567567567567568 [0.947368,0.117647]