10588184 32117 VAIBHAV JAISWAL 18 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. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22103935 description https://api.openml.org/data/download/22103935/description.xml -1 22103936 predictions https://api.openml.org/data/download/22103936/predictions.arff area_under_roc_curve 0.5073059722222223 [0.992475,0.407893,0.535013,0.613896,0.447218,0.386739,0.409167,0.443333,0.402165,0.435161] average_cost 0 f_measure 0.1311280214447002 [0.992443,0.004706,0.105528,0.193069,0.005277,0,0,0,0.005168,0.005089] kappa 0.033888888888888885 kb_relative_information_score 0.10938677533784937 mean_absolute_error 0.17315999999999504 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.1305 [0.985,0.005,0.105,0.195,0.005,0,0,0,0.005,0.005] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.13177970540052036 [1,0.004444,0.106061,0.191176,0.005587,0,0,0,0.005348,0.005181] predictive_accuracy 0.1305 prior_entropy 3.3219280948872383 relative_absolute_error 0.9619999999999429 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.38351531912036807 root_relative_squared_error 1.2783843970678739 total_cost 0 unweighted_recall 0.13049999999999998 [0.985,0.005,0.105,0.195,0.005,0,0,0,0.005,0.005] area_under_roc_curve 0.5052222222222222 [0.974722,0.4,0.523056,0.683472,0.409861,0.391667,0.402778,0.444444,0.394444,0.427778] area_under_roc_curve 0.5039305555555554 [1,0.399444,0.568194,0.592778,0.416667,0.380556,0.4,0.441667,0.412222,0.427778] area_under_roc_curve 0.49919444444444444 [0.975,0.380556,0.504444,0.632083,0.433194,0.394444,0.425,0.444444,0.383333,0.419444] area_under_roc_curve 0.49888888888888877 [1,0.408333,0.507917,0.54875,0.439722,0.377778,0.416667,0.438889,0.400833,0.45] area_under_roc_curve 0.5173194444444443 [1,0.402778,0.578333,0.655139,0.450556,0.400833,0.408333,0.444444,0.402222,0.430556] area_under_roc_curve 0.5174027777777777 [1,0.402778,0.612083,0.510139,0.568472,0.386111,0.416667,0.444444,0.391667,0.441667] area_under_roc_curve 0.5011527777777777 [0.974861,0.415417,0.503333,0.591528,0.454167,0.391667,0.413889,0.441667,0.391667,0.433333] area_under_roc_curve 0.507625 [1,0.420278,0.5225,0.639028,0.40875,0.377778,0.405556,0.444444,0.421806,0.436111] area_under_roc_curve 0.5187916666666667 [1,0.443333,0.520417,0.676944,0.477639,0.383333,0.397222,0.444444,0.400278,0.444306] area_under_roc_curve 0.5031111111111111 [1,0.405556,0.51,0.604028,0.412917,0.383333,0.405556,0.444444,0.423611,0.441667] 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 0.13663003663003662 [0.974359,0,0.153846,0.238095,0,0,0,0,0,0] f_measure 0.14357142857142857 [1,0,0.15,0.285714,0,0,0,0,0,0] f_measure 0.1177708256655625 [0.974359,0,0.045455,0.157895,0,0,0,0,0,0] f_measure 0.12549923195084486 [1,0,0.064516,0.190476,0,0,0,0,0,0] f_measure 0.129020979020979 [1,0,0.136364,0.153846,0,0,0,0,0,0] f_measure 0.1289232886136911 [1,0,0.177778,0.058824,0.052632,0,0,0,0,0] f_measure 0.11694809255784865 [0.974359,0,0,0.195122,0,0,0,0,0,0] f_measure 0.12577597840755736 [1,0,0.052632,0.205128,0,0,0,0,0,0] f_measure 0.1452136704433406 [1,0.04878,0.133333,0.217391,0,0,0,0,0,0.052632] f_measure 0.13497416872345971 [1,0,0.108108,0.195122,0,0,0,0,0.046512,0] kappa 0.03888888888888889 kappa 0.04999999999999998 kappa 0.016666666666666666 kappa 0.02777777777777777 kappa 0.03333333333333333 kappa 0.03333333333333333 kappa 0.016666666666666666 kappa 0.02777777777777777 kappa 0.05555555555555554 kappa 0.03888888888888889 kb_relative_information_score 0.1092541260624001 kb_relative_information_score 0.11362943237935864 kb_relative_information_score 0.09362943237935832 kb_relative_information_score 0.10039034496991536 kb_relative_information_score 0.1187772943538614 kb_relative_information_score 0.11315260067081992 kb_relative_information_score 0.09476565128687374 kb_relative_information_score 0.11445593835576996 kb_relative_information_score 0.12852153174162453 kb_relative_information_score 0.10729140117847344 mean_absolute_error 0.17339999999999983 mean_absolute_error 0.1721999999999998 mean_absolute_error 0.17559999999999984 mean_absolute_error 0.1741999999999998 mean_absolute_error 0.1717999999999998 mean_absolute_error 0.17299999999999982 mean_absolute_error 0.17539999999999986 mean_absolute_error 0.1727999999999998 mean_absolute_error 0.1701999999999998 mean_absolute_error 0.1729999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.13851674641148326 [1,0,0.157895,0.227273,0,0,0,0,0,0] precision 0.14227272727272727 [1,0,0.15,0.272727,0,0,0,0,0,0] precision 0.12083333333333332 [1,0,0.041667,0.166667,0,0,0,0,0,0] precision 0.1272727272727273 [1,0,0.090909,0.181818,0,0,0,0,0,0] precision 0.12828947368421054 [1,0,0.125,0.157895,0,0,0,0,0,0] precision 0.12869841269841267 [1,0,0.16,0.071429,0.055556,0,0,0,0,0] precision 0.11904761904761905 [1,0,0,0.190476,0,0,0,0,0,0] precision 0.12660818713450292 [1,0,0.055556,0.210526,0,0,0,0,0,0] precision 0.14154822954822954 [1,0.047619,0.12,0.192308,0,0,0,0,0,0.055556] precision 0.13516015101692852 [1,0,0.117647,0.190476,0,0,0,0,0.043478,0] predictive_accuracy 0.135 predictive_accuracy 0.145 predictive_accuracy 0.115 predictive_accuracy 0.125 predictive_accuracy 0.13 predictive_accuracy 0.13 predictive_accuracy 0.115 predictive_accuracy 0.125 predictive_accuracy 0.15 predictive_accuracy 0.135 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 relative_absolute_error 0.9633333333333334 relative_absolute_error 0.9566666666666667 relative_absolute_error 0.9755555555555557 relative_absolute_error 0.9677777777777777 relative_absolute_error 0.9544444444444443 relative_absolute_error 0.9611111111111112 relative_absolute_error 0.9744444444444447 relative_absolute_error 0.96 relative_absolute_error 0.9455555555555555 relative_absolute_error 0.961111111111111 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.3829360259886759 root_mean_squared_error 0.38136596596969663 root_mean_squared_error 0.3879175170058705 root_mean_squared_error 0.38538292645108174 root_mean_squared_error 0.3830926780819489 root_mean_squared_error 0.3823087757297757 root_mean_squared_error 0.3896151947755629 root_mean_squared_error 0.3787875393937872 root_mean_squared_error 0.3768288736283352 root_mean_squared_error 0.38672987989034396 root_relative_squared_error 1.2764534199622537 root_relative_squared_error 1.271219886565656 root_relative_squared_error 1.2930583900195691 root_relative_squared_error 1.2846097548369397 root_relative_squared_error 1.276975593606497 root_relative_squared_error 1.2743625857659198 root_relative_squared_error 1.2987173159185437 root_relative_squared_error 1.2626251313126247 root_relative_squared_error 1.2560962454277849 root_relative_squared_error 1.2890995996344807 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 0.13499999999999998 [0.95,0,0.15,0.25,0,0,0,0,0,0] unweighted_recall 0.145 [1,0,0.15,0.3,0,0,0,0,0,0] unweighted_recall 0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0] unweighted_recall 0.125 [1,0,0.05,0.2,0,0,0,0,0,0] unweighted_recall 0.12999999999999998 [1,0,0.15,0.15,0,0,0,0,0,0] unweighted_recall 0.13 [1,0,0.2,0.05,0.05,0,0,0,0,0] unweighted_recall 0.11499999999999999 [0.95,0,0,0.2,0,0,0,0,0,0] unweighted_recall 0.125 [1,0,0.05,0.2,0,0,0,0,0,0] unweighted_recall 0.15 [1,0.05,0.15,0.25,0,0,0,0,0,0.05] unweighted_recall 0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0] usercpu_time_millis 31.25 usercpu_time_millis 15.625 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 15.625 usercpu_time_millis_testing 15.625 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_testing 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_training 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 0 usercpu_time_millis_training 15.625 usercpu_time_millis_training 15.625 wall_clock_time_millis 28.983354568481445 wall_clock_time_millis 20.009279251098633 wall_clock_time_millis 13.991355895996094 wall_clock_time_millis 13.002634048461914 wall_clock_time_millis 13.988256454467773 wall_clock_time_millis 13.991355895996094 wall_clock_time_millis 14.99319076538086 wall_clock_time_millis 13.991355895996094 wall_clock_time_millis 13.988733291625977 wall_clock_time_millis 13.991117477416992 wall_clock_time_millis_testing 19.006967544555664 wall_clock_time_millis_testing 9.011983871459961 wall_clock_time_millis_testing 8.994340896606445 wall_clock_time_millis_testing 7.99560546875 wall_clock_time_millis_testing 8.994817733764648 wall_clock_time_millis_testing 8.994817733764648 wall_clock_time_millis_testing 9.996414184570312 wall_clock_time_millis_testing 8.99505615234375 wall_clock_time_millis_testing 7.99560546875 wall_clock_time_millis_testing 8.994817733764648 wall_clock_time_millis_training 9.976387023925781 wall_clock_time_millis_training 10.997295379638672 wall_clock_time_millis_training 4.997014999389648 wall_clock_time_millis_training 5.007028579711914 wall_clock_time_millis_training 4.993438720703125 wall_clock_time_millis_training 4.996538162231445 wall_clock_time_millis_training 4.996776580810547 wall_clock_time_millis_training 4.996299743652344 wall_clock_time_millis_training 5.993127822875977 wall_clock_time_millis_training 4.996299743652344 weighted_recall 0.135 [0.95,0,0.15,0.25,0,0,0,0,0,0] weighted_recall 0.145 [1,0,0.15,0.3,0,0,0,0,0,0] weighted_recall 0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.05,0.2,0,0,0,0,0,0] weighted_recall 0.13 [1,0,0.15,0.15,0,0,0,0,0,0] weighted_recall 0.13 [1,0,0.2,0.05,0.05,0,0,0,0,0] weighted_recall 0.115 [0.95,0,0,0.2,0,0,0,0,0,0] weighted_recall 0.125 [1,0,0.05,0.2,0,0,0,0,0,0] weighted_recall 0.15 [1,0.05,0.15,0.25,0,0,0,0,0,0.05] weighted_recall 0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]