10588254 32117 VAIBHAV JAISWAL 18 Supervised Classification 19176 sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.neural_network._multilayer_perceptron.MLPClassifier)(1) 8304110 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 19176 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"}}] 19176 verbose false 19176 activation "relu" 19177 alpha 0.0001 19177 batch_size "auto" 19177 beta_1 0.9 19177 beta_2 0.999 19177 early_stopping false 19177 epsilon 1e-08 19177 hidden_layer_sizes [100] 19177 learning_rate "constant" 19177 learning_rate_init 0.001 19177 max_fun 15000 19177 max_iter 5000 19177 momentum 0.9 19177 n_iter_no_change 10 19177 nesterovs_momentum true 19177 power_t 0.5 19177 random_state 0 19177 shuffle true 19177 solver "adam" 19177 tol 0.0001 19177 validation_fraction 0.1 19177 verbose false 19177 warm_start false 19177 openml-python Sklearn_1.0.2. 18 mfeat-morphological https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff -1 22104075 description https://api.openml.org/data/download/22104075/description.xml -1 22104076 predictions https://api.openml.org/data/download/22104076/predictions.arff area_under_roc_curve 0.509278888888889 [0.999797,0.375039,0.691672,0.764033,0.659447,0.309967,0.391864,0.208228,0.154597,0.538144] average_cost 0 f_measure 0.12528424181521852 [0.992443,0,0.069519,0.169492,0,0,0,0,0.016438,0.00495] kappa 0.027222222222222214 kb_relative_information_score 0.09925930739398094 mean_absolute_error 0.1735932661494544 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.1245 [0.985,0,0.065,0.175,0,0,0,0,0.015,0.005] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.12621156714705836 [1,0,0.074713,0.164319,0,0,0,0,0.018182,0.004902] predictive_accuracy 0.1245 prior_entropy 3.3219280948872383 relative_absolute_error 0.9644070341636057 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.3793466779582967 root_relative_squared_error 1.2644889265276362 total_cost 0 unweighted_recall 0.12449999999999999 [0.985,0,0.065,0.175,0,0,0,0,0.015,0.005] area_under_roc_curve 0.5410555555555555 [1,0.342222,0.685,0.796111,0.636667,0.331111,0.482083,0.252222,0.350556,0.534583] area_under_roc_curve 0.5034722222222222 [1,0.39,0.744167,0.765833,0.678611,0.23,0.380556,0.220278,0.094167,0.531111] area_under_roc_curve 0.5068888888888889 [0.999444,0.3425,0.653056,0.779444,0.672778,0.488889,0.347917,0.200556,0.086667,0.497639] area_under_roc_curve 0.4953888888888888 [1,0.398056,0.655278,0.708333,0.661944,0.247778,0.364167,0.212222,0.153611,0.5525] area_under_roc_curve 0.5164166666666666 [1,0.409444,0.695,0.8,0.702222,0.326111,0.379722,0.169722,0.161389,0.520556] area_under_roc_curve 0.4975555555555555 [1,0.405833,0.696111,0.689167,0.671111,0.289722,0.431667,0.145278,0.065,0.581667] area_under_roc_curve 0.4772777777777778 [0.999167,0.334167,0.693889,0.778056,0.656944,0.080556,0.399306,0.213056,0.0575,0.560139] area_under_roc_curve 0.5167222222222223 [1,0.375,0.682222,0.789722,0.628889,0.321667,0.37,0.215556,0.248056,0.536111] area_under_roc_curve 0.5201944444444444 [1,0.361667,0.696944,0.767222,0.644167,0.375833,0.3675,0.241944,0.196667,0.55] area_under_roc_curve 0.5023611111111111 [1,0.385833,0.700556,0.750278,0.639722,0.263611,0.394583,0.211667,0.163611,0.51375] 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 0.12886446886446884 [0.974359,0,0.114286,0.2,0,0,0,0,0,0] f_measure 0.11969111969111969 [1,0,0.054054,0.142857,0,0,0,0,0,0] f_measure 0.1171978021978022 [0.974359,0,0.047619,0.15,0,0,0,0,0,0] f_measure 0.12151315789473685 [1,0,0.0625,0.1,0,0,0,0,0.052632,0] f_measure 0.13779904306220095 [1,0,0.105263,0.272727,0,0,0,0,0,0] f_measure 0.11449631449631449 [1,0,0.090909,0.054054,0,0,0,0,0,0] f_measure 0.11694809255784865 [0.974359,0,0,0.195122,0,0,0,0,0,0] f_measure 0.11941391941391942 [1,0,0,0.142857,0,0,0,0,0.051282,0] f_measure 0.1375159119839971 [1,0,0.111111,0.212766,0,0,0,0,0,0.051282] f_measure 0.1360797342192691 [1,0,0.114286,0.2,0,0,0,0,0.046512,0] kappa 0.02777777777777777 kappa 0.02222222222222221 kappa 0.016666666666666666 kappa 0.02222222222222221 kappa 0.04444444444444445 kappa 0.016666666666666666 kappa 0.016666666666666666 kappa 0.02222222222222221 kappa 0.04444444444444445 kappa 0.03888888888888889 kb_relative_information_score 0.10712045254106675 kb_relative_information_score 0.10602854842014578 kb_relative_information_score 0.0882299696044493 kb_relative_information_score 0.09249827536613915 kb_relative_information_score 0.11080064845915048 kb_relative_information_score 0.0879129614729517 kb_relative_information_score 0.08332969874936685 kb_relative_information_score 0.09639733710284419 kb_relative_information_score 0.11898257605772279 kb_relative_information_score 0.10129260616593969 mean_absolute_error 0.17328097521045416 mean_absolute_error 0.17277615854664327 mean_absolute_error 0.17551123684677275 mean_absolute_error 0.17435074178365387 mean_absolute_error 0.17188493265127835 mean_absolute_error 0.1753670482738938 mean_absolute_error 0.17555414988280943 mean_absolute_error 0.17430722754649955 mean_absolute_error 0.17000739359349837 mean_absolute_error 0.17289279715904218 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 0.13333333333333333 [1,0,0.133333,0.2,0,0,0,0,0,0] precision 0.1195187165775401 [1,0,0.058824,0.136364,0,0,0,0,0,0] precision 0.11954545454545455 [1,0,0.045455,0.15,0,0,0,0,0,0] precision 0.1238888888888889 [1,0,0.083333,0.1,0,0,0,0,0.055556,0] precision 0.1361111111111111 [1,0,0.111111,0.25,0,0,0,0,0,0] precision 0.1142156862745098 [1,0,0.083333,0.058824,0,0,0,0,0,0] precision 0.11904761904761905 [1,0,0,0.190476,0,0,0,0,0,0] precision 0.11889952153110048 [1,0,0,0.136364,0,0,0,0,0.052632,0] precision 0.13628167641325536 [1,0,0.125,0.185185,0,0,0,0,0,0.052632] precision 0.13768115942028986 [1,0,0.133333,0.2,0,0,0,0,0.043478,0] predictive_accuracy 0.125 predictive_accuracy 0.12 predictive_accuracy 0.115 predictive_accuracy 0.12 predictive_accuracy 0.14 predictive_accuracy 0.115 predictive_accuracy 0.115 predictive_accuracy 0.12 predictive_accuracy 0.14 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 0.9626720845025241 relative_absolute_error 0.9598675474813525 relative_absolute_error 0.9750624269265163 relative_absolute_error 0.9686152321314114 relative_absolute_error 0.9549162925071031 relative_absolute_error 0.974261379299411 relative_absolute_error 0.9753008326822757 relative_absolute_error 0.9683734863694431 relative_absolute_error 0.9444855199638809 relative_absolute_error 0.9605155397724576 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 0.3780870156408469 root_mean_squared_error 0.37648636243472344 root_mean_squared_error 0.38111603669143884 root_mean_squared_error 0.3814451626384764 root_mean_squared_error 0.3777447471340074 root_mean_squared_error 0.38240845942729795 root_mean_squared_error 0.38469277356898096 root_mean_squared_error 0.37843986300172455 root_mean_squared_error 0.37373140261315946 root_mean_squared_error 0.37919606760577684 root_relative_squared_error 1.260290052136157 root_relative_squared_error 1.254954541449079 root_relative_squared_error 1.2703867889714635 root_relative_squared_error 1.271483875461589 root_relative_squared_error 1.2591491571133588 root_relative_squared_error 1.2746948647576608 root_relative_squared_error 1.2823092452299374 root_relative_squared_error 1.2614662100057492 root_relative_squared_error 1.2457713420438656 root_relative_squared_error 1.263986892019257 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 0.125 [0.95,0,0.1,0.2,0,0,0,0,0,0] unweighted_recall 0.12 [1,0,0.05,0.15,0,0,0,0,0,0] unweighted_recall 0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0] unweighted_recall 0.12000000000000002 [1,0,0.05,0.1,0,0,0,0,0.05,0] unweighted_recall 0.14 [1,0,0.1,0.3,0,0,0,0,0,0] unweighted_recall 0.11500000000000002 [1,0,0.1,0.05,0,0,0,0,0,0] unweighted_recall 0.11499999999999999 [0.95,0,0,0.2,0,0,0,0,0,0] unweighted_recall 0.12 [1,0,0,0.15,0,0,0,0,0.05,0] unweighted_recall 0.14 [1,0,0.1,0.25,0,0,0,0,0,0.05] unweighted_recall 0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0] usercpu_time_millis 4875 usercpu_time_millis 4265.625 usercpu_time_millis 5437.5 usercpu_time_millis 5250 usercpu_time_millis 5171.875 usercpu_time_millis 5062.5 usercpu_time_millis 5078.125 usercpu_time_millis 5875 usercpu_time_millis 5078.125 usercpu_time_millis 5578.125 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 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_training 4875 usercpu_time_millis_training 4265.625 usercpu_time_millis_training 5437.5 usercpu_time_millis_training 5250 usercpu_time_millis_training 5171.875 usercpu_time_millis_training 5062.5 usercpu_time_millis_training 5078.125 usercpu_time_millis_training 5875 usercpu_time_millis_training 5078.125 usercpu_time_millis_training 5578.125 wall_clock_time_millis 4903.190135955811 wall_clock_time_millis 4295.536518096924 wall_clock_time_millis 5454.87380027771 wall_clock_time_millis 5251.988410949707 wall_clock_time_millis 5172.036170959473 wall_clock_time_millis 5058.100461959839 wall_clock_time_millis 5081.106424331665 wall_clock_time_millis 5863.6579513549805 wall_clock_time_millis 5087.063312530518 wall_clock_time_millis 5589.816093444824 wall_clock_time_millis_testing 0.9982585906982422 wall_clock_time_millis_testing 1.0004043579101562 wall_clock_time_millis_testing 0.9987354278564453 wall_clock_time_millis_testing 1.0006427764892578 wall_clock_time_millis_testing 0.99945068359375 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0.99945068359375 wall_clock_time_millis_testing 0.9992122650146484 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 1.0001659393310547 wall_clock_time_millis_training 4902.191877365112 wall_clock_time_millis_training 4294.536113739014 wall_clock_time_millis_training 5453.8750648498535 wall_clock_time_millis_training 5250.987768173218 wall_clock_time_millis_training 5171.036720275879 wall_clock_time_millis_training 5058.100461959839 wall_clock_time_millis_training 5080.106973648071 wall_clock_time_millis_training 5862.658739089966 wall_clock_time_millis_training 5087.063312530518 wall_clock_time_millis_training 5588.815927505493 weighted_recall 0.125 [0.95,0,0.1,0.2,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0.05,0.15,0,0,0,0,0,0] weighted_recall 0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0.05,0.1,0,0,0,0,0.05,0] weighted_recall 0.14 [1,0,0.1,0.3,0,0,0,0,0,0] weighted_recall 0.115 [1,0,0.1,0.05,0,0,0,0,0,0] weighted_recall 0.115 [0.95,0,0,0.2,0,0,0,0,0,0] weighted_recall 0.12 [1,0,0,0.15,0,0,0,0,0.05,0] weighted_recall 0.14 [1,0,0.1,0.25,0,0,0,0,0,0.05] weighted_recall 0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]