10559339 8323 Heinrich Peters 2079 Supervised Classification 18298 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4) 8276071 copy true 17405 with_mean true 17405 with_std true 17405 add_indicator false 17407 copy true 17407 fill_value null 17407 missing_values NaN 17407 strategy "most_frequent" 17407 verbose 0 17407 categorical_features null 17408 categories null 17408 drop null 17408 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 17408 handle_unknown "ignore" 17408 n_values null 17408 sparse true 17408 C 49.7233002061335 17495 cache_size 200 17495 class_weight null 17495 coef0 0.46757379405725374 17495 decision_function_shape "ovr" 17495 degree 1 17495 gamma 0.003603475971010618 17495 kernel "rbf" 17495 max_iter -1 17495 probability true 17495 random_state 1 17495 shrinking true 17495 tol 0.001 17495 verbose false 17495 memory null 18298 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] 18298 verbose false 18298 n_jobs null 18299 remainder "drop" 18299 sparse_threshold 0.3 18299 transformer_weights null 18299 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, true, true, true, true, false, true, true, true, true, true, true, true, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, false, false, false, false, true, false, false, false, false, false, false, false, false, false]}}] 18299 verbose false 18299 memory null 18300 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18300 verbose false 18300 memory null 18301 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18301 verbose false 18301 openml-python Sklearn_0.21.2. 188 eucalyptus https://www.openml.org/data/download/3625/dataset_194_eucalyptus.arff -1 22043643 description https://api.openml.org/data/download/22043643/description.xml -1 22043644 predictions https://api.openml.org/data/download/22043644/predictions.arff area_under_roc_curve 0.9152699628981743 [0.979966,0.929349,0.881328,0.879803,0.904324] average_cost 0 f_measure 0.674664040439913 [0.857143,0.604651,0.539419,0.70021,0.548571] kappa 0.5871662553286965 kb_relative_information_score 0.567159933216641 mean_absolute_error 0.1738943134269862 mean_prior_absolute_error 0.313229771753801 weighted_recall 0.6807065217391305 [0.866667,0.607477,0.5,0.780374,0.457143] number_of_instances 736 [180,107,130,214,105] precision 0.6807322031051407 [0.847826,0.601852,0.585586,0.634981,0.685714] predictive_accuracy 0.6807065217391305 prior_entropy 2.2620863489531073 relative_absolute_error 0.5551653422129597 root_mean_prior_squared_error 0.39571712668407916 root_mean_squared_error 0.2909928462497165 root_relative_squared_error 0.7353557039294654 total_cost 0 unweighted_recall 0.6423319982198488 [0.866667,0.607477,0.5,0.780374,0.457143] area_under_roc_curve 0.9187239081686963 [0.982143,0.922078,0.865069,0.884996,0.939394] area_under_roc_curve 0.9228703373073928 [0.950397,0.922078,0.93947,0.948787,0.809524] area_under_roc_curve 0.9064240236115235 [0.992063,0.948052,0.846154,0.850524,0.907813] area_under_roc_curve 0.9269642491978558 [0.972222,0.883117,0.905422,0.905594,0.96875] area_under_roc_curve 0.8974438811785124 [0.974206,0.937951,0.800757,0.854021,0.935937] area_under_roc_curve 0.9222206846438404 [0.962302,0.894661,0.92686,0.916958,0.885938] area_under_roc_curve 0.9006857506415614 [0.989899,0.917889,0.85,0.846154,0.901587] area_under_roc_curve 0.9234324373520131 [0.994949,0.952381,0.942308,0.867216,0.865103] area_under_roc_curve 0.913572995963628 [1,0.973016,0.869231,0.837912,0.914956] area_under_roc_curve 0.9247847993318609 [0.981818,0.949206,0.871795,0.893773,0.931085] 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 0.6388217164532954 [0.8,0.5,0.583333,0.666667,0.526316] f_measure 0.7478179650238475 [0.823529,0.666667,0.666667,0.84,0.625] f_measure 0.6120030856055702 [0.888889,0.583333,0.434783,0.612245,0.375] f_measure 0.7092431567221482 [0.857143,0.666667,0.5,0.734694,0.705882] f_measure 0.670904172672106 [0.864865,0.631579,0.4,0.693878,0.666667] f_measure 0.6830989152417724 [0.777778,0.47619,0.583333,0.77551,0.666667] f_measure 0.6381142811997882 [0.857143,0.608696,0.583333,0.716981,0.181818] f_measure 0.6977609002784273 [0.918919,0.631579,0.666667,0.651163,0.521739] f_measure 0.6483521557115262 [0.972973,0.7,0.416667,0.595745,0.444444] f_measure 0.670151988424711 [0.810811,0.555556,0.551724,0.697674,0.631579] kappa 0.5468676401318889 kappa 0.6857008022652195 kappa 0.5095857988165681 kappa 0.6334041047416843 kappa 0.5787476280834914 kappa 0.5971597633136094 kappa 0.5691096901131333 kappa 0.6139423076923077 kappa 0.5571463237078379 kappa 0.5777295733911787 kb_relative_information_score 0.5514713826917055 kb_relative_information_score 0.6104285134703616 kb_relative_information_score 0.5658884377699469 kb_relative_information_score 0.5810625542277111 kb_relative_information_score 0.5356665993806013 kb_relative_information_score 0.5467419949777624 kb_relative_information_score 0.5512488281397528 kb_relative_information_score 0.5765878099586764 kb_relative_information_score 0.579071453543678 kb_relative_information_score 0.5733833571915662 mean_absolute_error 0.17797142283770592 mean_absolute_error 0.1612616769474264 mean_absolute_error 0.17461177782744833 mean_absolute_error 0.1709657794390945 mean_absolute_error 0.185398360990426 mean_absolute_error 0.1788606193305983 mean_absolute_error 0.17783531091989446 mean_absolute_error 0.17127152331630194 mean_absolute_error 0.1674389790018512 mean_absolute_error 0.17324955000417228 mean_prior_absolute_error 0.3137031768610717 mean_prior_absolute_error 0.3137031768610717 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.31330486384559936 mean_prior_absolute_error 0.3133196531898768 mean_prior_absolute_error 0.3133196531898768 mean_prior_absolute_error 0.3133196531898768 number_of_instances 74 [18,11,13,21,11] number_of_instances 74 [18,11,13,21,11] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 73 [18,11,13,21,10] number_of_instances 73 [18,10,13,21,11] number_of_instances 73 [18,10,13,21,11] number_of_instances 73 [18,10,13,21,11] precision 0.6415506415506416 [0.727273,0.555556,0.636364,0.625,0.625] precision 0.786225307777032 [0.875,0.615385,0.727273,0.724138,1] precision 0.6168283668283668 [0.888889,0.538462,0.5,0.555556,0.5] precision 0.7377521954727836 [0.882353,0.5625,0.714286,0.666667,0.857143] precision 0.6780596385859543 [0.842105,0.75,0.416667,0.62963,0.75] precision 0.6858676858676859 [0.777778,0.5,0.636364,0.703704,0.75] precision 0.7265821490489098 [0.882353,0.583333,0.636364,0.59375,1] precision 0.6998645430512771 [0.894737,0.666667,0.727273,0.636364,0.5] precision 0.6514401244033543 [0.947368,0.7,0.454545,0.538462,0.571429] precision 0.6784754538900177 [0.789474,0.625,0.5,0.681818,0.75] predictive_accuracy 0.6486486486486487 predictive_accuracy 0.7567567567567568 predictive_accuracy 0.6216216216216216 predictive_accuracy 0.7162162162162162 predictive_accuracy 0.6756756756756757 predictive_accuracy 0.6891891891891891 predictive_accuracy 0.6712328767123288 predictive_accuracy 0.6986301369863014 predictive_accuracy 0.6575342465753425 predictive_accuracy 0.6712328767123288 prior_entropy 2.270428889699664 prior_entropy 2.270428889699664 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2631003912333214 prior_entropy 2.263469802844284 prior_entropy 2.263469802844284 prior_entropy 2.263469802844284 relative_absolute_error 0.5673242605270885 relative_absolute_error 0.5140581570165088 relative_absolute_error 0.5580290374979776 relative_absolute_error 0.5463770573355463 relative_absolute_error 0.59250109141794 relative_absolute_error 0.5716075999751733 relative_absolute_error 0.5676110761163733 relative_absolute_error 0.5466351107330908 relative_absolute_error 0.5344030522732018 relative_absolute_error 0.5529482374959103 root_mean_prior_squared_error 0.39631483628344655 root_mean_prior_squared_error 0.39631483628344655 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.3958119963352585 root_mean_prior_squared_error 0.3958306781784102 root_mean_prior_squared_error 0.3958306781784102 root_mean_prior_squared_error 0.3958306781784102 root_mean_squared_error 0.2984925092653696 root_mean_squared_error 0.2771167976863458 root_mean_squared_error 0.2934741657964862 root_mean_squared_error 0.28176481617050514 root_mean_squared_error 0.30116815063106406 root_mean_squared_error 0.3020226994085734 root_mean_squared_error 0.2959251124949918 root_mean_squared_error 0.28450345347562983 root_mean_squared_error 0.2832973085468397 root_mean_squared_error 0.29085215306814755 root_relative_squared_error 0.7531701615426936 root_relative_squared_error 0.6992339733861246 root_relative_squared_error 0.7423891615479704 root_relative_squared_error 0.7127685159708317 root_relative_squared_error 0.7618523089592694 root_relative_squared_error 0.764014024791105 root_relative_squared_error 0.7476405850123323 root_relative_squared_error 0.7187503878802376 root_relative_squared_error 0.7157032644628694 root_relative_squared_error 0.7347893154887142 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 0.6101454101454101 [0.888889,0.454545,0.538462,0.714286,0.454545] unweighted_recall 0.714996114996115 [0.777778,0.727273,0.615385,1,0.454545] unweighted_recall 0.5783372183372182 [0.888889,0.636364,0.384615,0.681818,0.3] unweighted_recall 0.690862470862471 [0.833333,0.818182,0.384615,0.818182,0.6] unweighted_recall 0.6383372183372183 [0.888889,0.545455,0.384615,0.772727,0.6] unweighted_recall 0.6468842268842269 [0.777778,0.454545,0.538462,0.863636,0.6] unweighted_recall 0.6025840825840826 [0.833333,0.636364,0.538462,0.904762,0.1] unweighted_recall 0.6743900543900543 [0.944444,0.6,0.615385,0.666667,0.545455] unweighted_recall 0.622983682983683 [1,0.7,0.384615,0.666667,0.363636] unweighted_recall 0.6416916416916417 [0.833333,0.5,0.615385,0.714286,0.545455] usercpu_time_millis 174.16000000000054 usercpu_time_millis 192.54199999999955 usercpu_time_millis 173.1739999999995 usercpu_time_millis 188.7480000000004 usercpu_time_millis 177.8720000000007 usercpu_time_millis 197.92400000000043 usercpu_time_millis 203.35999999999999 usercpu_time_millis 211.90599999999992 usercpu_time_millis 196.47599999999966 usercpu_time_millis 200.52200000000033 usercpu_time_millis_testing 7.103999999999999 usercpu_time_millis_testing 7.6019999999994425 usercpu_time_millis_testing 7.163999999999504 usercpu_time_millis_testing 7.355999999999696 usercpu_time_millis_testing 7.716000000000278 usercpu_time_millis_testing 7.810000000000095 usercpu_time_millis_testing 10.796000000000028 usercpu_time_millis_testing 7.305999999999813 usercpu_time_millis_testing 7.678000000000296 usercpu_time_millis_testing 9.999999999999787 usercpu_time_millis_training 167.05600000000055 usercpu_time_millis_training 184.9400000000001 usercpu_time_millis_training 166.01 usercpu_time_millis_training 181.39200000000068 usercpu_time_millis_training 170.1560000000004 usercpu_time_millis_training 190.11400000000035 usercpu_time_millis_training 192.56399999999996 usercpu_time_millis_training 204.6000000000001 usercpu_time_millis_training 188.79799999999935 usercpu_time_millis_training 190.52200000000053 wall_clock_time_millis 87.62979507446289 wall_clock_time_millis 97.4729061126709 wall_clock_time_millis 87.13102340698242 wall_clock_time_millis 94.65479850769043 wall_clock_time_millis 90.2547836303711 wall_clock_time_millis 113.32297325134277 wall_clock_time_millis 105.75604438781738 wall_clock_time_millis 110.23783683776855 wall_clock_time_millis 103.07002067565918 wall_clock_time_millis 106.97293281555176 wall_clock_time_millis_testing 3.5598278045654297 wall_clock_time_millis_testing 3.8080215454101562 wall_clock_time_millis_testing 3.626108169555664 wall_clock_time_millis_testing 3.6809444427490234 wall_clock_time_millis_testing 3.8809776306152344 wall_clock_time_millis_testing 3.957033157348633 wall_clock_time_millis_testing 5.515098571777344 wall_clock_time_millis_testing 3.6649703979492188 wall_clock_time_millis_testing 3.9539337158203125 wall_clock_time_millis_testing 5.7048797607421875 wall_clock_time_millis_training 84.06996726989746 wall_clock_time_millis_training 93.66488456726074 wall_clock_time_millis_training 83.50491523742676 wall_clock_time_millis_training 90.9738540649414 wall_clock_time_millis_training 86.37380599975586 wall_clock_time_millis_training 109.36594009399414 wall_clock_time_millis_training 100.24094581604004 wall_clock_time_millis_training 106.57286643981934 wall_clock_time_millis_training 99.11608695983887 wall_clock_time_millis_training 101.26805305480957 weighted_recall 0.6486486486486487 [0.888889,0.454545,0.538462,0.714286,0.454545] weighted_recall 0.7567567567567568 [0.777778,0.727273,0.615385,1,0.454545] weighted_recall 0.6216216216216216 [0.888889,0.636364,0.384615,0.681818,0.3] weighted_recall 0.7162162162162162 [0.833333,0.818182,0.384615,0.818182,0.6] weighted_recall 0.6756756756756757 [0.888889,0.545455,0.384615,0.772727,0.6] weighted_recall 0.6891891891891891 [0.777778,0.454545,0.538462,0.863636,0.6] weighted_recall 0.6712328767123288 [0.833333,0.636364,0.538462,0.904762,0.1] weighted_recall 0.6986301369863014 [0.944444,0.6,0.615385,0.666667,0.545455] weighted_recall 0.6575342465753424 [1,0.7,0.384615,0.666667,0.363636] weighted_recall 0.6712328767123288 [0.833333,0.5,0.615385,0.714286,0.545455]