6054702 1 Jan van Rijn 9954 Supervised Classification 6952 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1) 4089355 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "most_frequent" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse true 6948 threshold 0.0 6949 C 0.7292790113698648 6953 cache_size 200 6953 class_weight null 6953 coef0 0.0 6953 decision_function_shape null 6953 degree 3 6953 gamma 0.051789453316451683 6953 kernel "rbf" 6953 max_iter -1 6953 probability true 6953 random_state 25123 6953 shrinking false 6953 tol 0.007053641701114141 6953 verbose false 6953 openml-pimp openml-python Sklearn_0.18.1. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 13032554 description https://api.openml.org/data/download/13032554/description.xml -1 13032555 predictions https://api.openml.org/data/download/13032555/predictions.arff area_under_roc_curve 0.38619949494949496 [0.391927,0.318655,0.311395,0.302794,0.309343,0.313565,0.308791,0.321654,0.315065,0.301491,0.332071,0.355824,0.350931,0.448509,0.381471,0.474905,0.343868,0.357876,0.371173,0.430279,0.349313,0.431424,0.435764,0.347617,0.378551,0.355863,0.446772,0.394137,0.474353,0.363123,0.348682,0.356297,0.38155,0.315696,0.442669,0.31467,0.358546,0.379025,0.34667,0.354009,0.498777,0.469184,0.309856,0.417456,0.313763,0.449732,0.317787,0.362453,0.462831,0.448193,0.461253,0.335306,0.422033,0.375197,0.408183,0.352115,0.301136,0.423019,0.361545,0.445391,0.373658,0.369634,0.316406,0.429569,0.422546,0.442077,0.39319,0.325955,0.437105,0.486664,0.488479,0.310803,0.457663,0.427478,0.442195,0.419547,0.453401,0.490767,0.455137,0.402699,0.411577,0.359848,0.452809,0.361664,0.448509,0.42511,0.330177,0.398003,0.458886,0.423453,0.348682,0.315459,0.360559,0.388218,0.417693,0.341974,0.393624,0.321023,0.394807,0.37137] average_cost 0 kappa -0.00883838383838384 kb_relative_information_score 66.56715622721725 mean_absolute_error 0.019779175177797738 mean_prior_absolute_error 0.019800000000000036 number_of_instances 1600 [16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] predictive_accuracy 0.00125 prior_entropy 6.6438561897747395 recall 0.00125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.125] relative_absolute_error 0.9989482413029143 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09946577579597214 root_relative_squared_error 0.9996686599904636 total_cost 0 area_under_roc_curve 0.04809803160576389 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[0.107595,0.018987,0,0.006289,0.006329,0.012658,0.044025,0.050633,0.022152,0,0.012658,0.015823,0.012579,0.028481,0.060127,0.123418,0.012658,0.107595,0.056604,0.041139,0.113208,0.125786,0.231013,0.012579,0.044025,0.041139,0.139241,0.050314,0.006329,0.022152,0.08805,0,0.113924,0.012658,0.031447,0,0.050314,0.150943,0.006289,0.006329,0.18038,0.025157,0,0.006289,0.006329,0.18239,0,0.069182,0.022152,0.009494,0.03481,0,0.012579,0.006329,0,0.028481,0,0.006329,0.069182,0.060127,0.018868,0.062893,0.003165,0.069182,0.006329,0.044304,0.132911,0,0.012579,0.06962,0.06962,0.006329,0.025157,0.028481,0.056604,0.009494,0.012658,0.03481,0.025316,0.044304,0.018868,0.025316,0.006329,0.031646,0.08805,0.031447,0,0.015823,0.085443,0.075472,0.075949,0,0,0.075949,0.047468,0.062893,0.050633,0.022152,0.081761,0.03481] area_under_roc_curve 0.04507055568824141 [0.231013,0.022152,0,0,0.009494,0.03481,0.012579,0.015823,0.022152,0,0.018987,0.018987,0.044025,0.085443,0.018987,0.117089,0.009494,0.082278,0.144654,0.091772,0.025157,0.012579,0.03481,0,0.025157,0.047468,0.18038,0.044025,0.006329,0.012658,0.025157,0,0.091772,0.006329,0.012579,0,0.044025,0.119497,0.006289,0,0.10443,0,0,0.006289,0,0.106918,0.006329,0.025157,0,0.006329,0.028481,0.006289,0.044025,0.14557,0.012579,0.072785,0,0.003165,0.044025,0.044304,0.006289,0.025157,0.006329,0.018868,0.006329,0.031646,0.098101,0.015823,0,0.161392,0.161392,0.006329,0.144654,0.044304,0.050314,0.006329,0.006329,0.142405,0.003165,0.056962,0.100629,0.03481,0.006329,0.015823,0.006289,0.025157,0,0.031646,0.041139,0.081761,0.10443,0,0.018868,0.075949,0.012658,0.069182,0.120253,0.025316,0.308176,0.012658] area_under_roc_curve 0.04718697754955818 [0.101266,0.018868,0.009494,0,0.018868,0.003165,0,0.037975,0.031447,0,0.022152,0.015823,0.069182,0.226415,0.037736,0.183544,0.022152,0.066456,0.069182,0.132911,0.028481,0.047468,0,0.006329,0.079114,0.041139,0.177215,0,0.018868,0.03481,0.037736,0,0.167722,0.018987,0.062893,0,0.072785,0.098101,0,0,0.218354,0.003165,0,0.031447,0,0.289308,0,0.018987,0,0.009494,0.037736,0.031447,0.006329,0.044025,0.009494,0.015823,0,0.028481,0.028481,0.031447,0,0.063291,0.012579,0,0.003165,0.022152,0.119497,0,0.03481,0.06962,0.10443,0,0.037736,0.018868,0.14557,0.018868,0.025316,0.126582,0.009494,0.056604,0.025157,0.012658,0.009494,0.037975,0.176101,0.037736,0.018868,0.031447,0.03481,0.053797,0.132075,0.009494,0,0.08805,0.060127,0.050314,0.037975,0,0.232704,0.151899] area_under_roc_curve 0.048946142823023675 [0.221519,0,0.012658,0,0,0.03481,0.006289,0.012658,0,0.003165,0.018987,0.025316,0.050314,0.044025,0.037736,0.167722,0.037975,0.094937,0.075472,0.148734,0.03481,0.066456,0.012658,0,0.063291,0.047468,0.193038,0.018868,0.012579,0.018987,0.025157,0,0.091772,0.009494,0.025157,0.003165,0.053797,0.082278,0.006329,0,0.212025,0.009494,0,0.031447,0.006289,0.138365,0,0.053797,0.018987,0.012658,0.069182,0.012579,0.041139,0.069182,0.053797,0.047468,0,0.003165,0.031646,0.025157,0.018987,0.088608,0.012579,0.006289,0,0.053797,0.144654,0,0.015823,0.050633,0.123418,0.006329,0.081761,0.056604,0.047468,0.044025,0.012658,0.246835,0.003165,0.069182,0.037736,0,0.012658,0.041139,0.157233,0.012579,0,0.018868,0.060127,0.053797,0.050314,0.006329,0.012579,0.044025,0.03481,0.018868,0.126582,0.012579,0.213836,0.14557] area_under_roc_curve 0.045885827163442416 [0.091772,0.037736,0,0,0,0.003165,0.006329,0.028481,0.006289,0,0.006289,0,0.056962,0.012579,0,0.237342,0.044025,0.106918,0.041139,0.142405,0.022152,0.025316,0.022152,0.018987,0.022152,0.144654,0.075472,0.10443,0,0,0.085443,0.006289,0.113208,0.031447,0.018987,0,0.044304,0.075949,0.003165,0,0.183544,0.012658,0,0.012658,0.075472,0.075949,0.009494,0.079114,0.012579,0.012579,0.100629,0.015823,0.041139,0.100629,0.050633,0.060127,0,0.006329,0.03481,0.012579,0.022152,0.132911,0.012579,0,0.012658,0.069182,0.132075,0.006329,0.044304,0.018987,0.125786,0,0.079114,0.081761,0.037975,0.006289,0,0.264151,0.031447,0.025157,0.142405,0.018868,0.009494,0.012658,0.056962,0.012658,0,0.044025,0.044025,0.072785,0.037736,0,0.012658,0.132075,0.031447,0.015823,0.132911,0.050314,0.155063,0.056962] area_under_roc_curve 0.04315813828516839 [0.056962,0.025157,0,0,0,0.006329,0.009494,0.015823,0.018868,0,0.050314,0,0.050633,0.006289,0.056604,0.158228,0.025157,0.150943,0.066456,0.075949,0.025316,0.031646,0.120253,0.012658,0.025316,0.037736,0.132075,0.022152,0.119497,0.006329,0.066456,0,0.09434,0.012579,0.018987,0,0.053797,0.094937,0.003165,0,0.177215,0.003165,0,0.022152,0.025157,0.136076,0,0.047468,0.012579,0.037736,0.283019,0.041139,0.066456,0.069182,0.012658,0.047468,0,0,0.044304,0.062893,0.003165,0.110759,0.012579,0.006329,0.003165,0.069182,0.18239,0,0.03481,0.009494,0.132075,0,0.085443,0.018868,0.044304,0.012579,0,0.031447,0,0.031447,0.075949,0.018868,0.015823,0.022152,0.056962,0.03481,0,0.031447,0.069182,0.072785,0.037736,0,0.003165,0.031447,0.025157,0.018987,0.072785,0.037736,0.139241,0.142405] area_under_roc_curve 0.0449287477111695 [0.044025,0.03481,0.012579,0,0,0.018868,0.012658,0,0.022152,0,0.025157,0.006289,0.015823,0.056962,0.018987,0.169811,0.012579,0.09434,0.060127,0.119497,0.012658,0.044304,0.125786,0.015823,0.047468,0.025157,0.132075,0.006329,0.003165,0.018868,0.050633,0,0.075472,0.012579,0.009494,0,0.044304,0.044304,0.006329,0,0.295597,0,0,0.028481,0.012658,0.272152,0,0.03481,0.025157,0.018868,0.091772,0.015823,0.025316,0.151899,0.037975,0.119497,0,0.044025,0.012658,0.025316,0.009494,0.091772,0,0.006329,0.006289,0.018868,0.148734,0,0.018987,0.132075,0.069182,0.006289,0.158228,0.022152,0.041139,0.050633,0.006289,0.125786,0.018868,0.047468,0.094937,0.037736,0.012579,0.018868,0.03481,0.012658,0,0.03481,0.125786,0.091772,0.072785,0.006329,0.006329,0.088608,0.025157,0.085443,0.09434,0.006329,0.148734,0.106918] area_under_roc_curve 0.04323600827959559 [0.09434,0.053797,0,0,0,0,0.003165,0,0.015823,0,0.025157,0.006289,0.037975,0.050633,0.031646,0.220126,0.031447,0.025157,0.06962,0.132075,0.06962,0.120253,0.006289,0.018987,0.050633,0.012579,0.132075,0.041139,0.025316,0.044025,0.028481,0,0.144654,0,0.022152,0.006329,0.03481,0.047468,0,0,0.138365,0.006329,0,0.012658,0.012658,0.041139,0,0.041139,0.012579,0.012579,0.053797,0.012658,0.047468,0.110759,0.009494,0.037736,0,0.018868,0.031646,0.060127,0.012658,0.050633,0.015823,0.012658,0.018868,0.037736,0.136076,0,0,0.056604,0.163522,0,0.047468,0.044304,0.132911,0.03481,0.006289,0.194969,0.012579,0.022152,0.050633,0.025157,0.037736,0.006289,0.053797,0.009494,0.003165,0.050633,0.037736,0.107595,0.088608,0,0.006329,0.123418,0.006289,0.047468,0.163522,0.044304,0.199367,0.132075] 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 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.006329113924050633 kappa -0.006329113924050633 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kb_relative_information_score 6.830678547158913 kb_relative_information_score 6.83134817070723 kb_relative_information_score 6.56545498928418 kb_relative_information_score 6.571955071061718 kb_relative_information_score 6.397383464755997 kb_relative_information_score 6.404116740901729 kb_relative_information_score 6.675005908502296 kb_relative_information_score 6.6786649869856 kb_relative_information_score 6.804644705159919 kb_relative_information_score 6.807903642699648 mean_absolute_error 0.01977856212365641 mean_absolute_error 0.019778516591957677 mean_absolute_error 0.019779505095481563 mean_absolute_error 0.019779468162402624 mean_absolute_error 0.019780150098913447 mean_absolute_error 0.01978009916715316 mean_absolute_error 0.019779116226949243 mean_absolute_error 0.01977907723390852 mean_absolute_error 0.019778620453465852 mean_absolute_error 0.019778636624088807 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] predictive_accuracy 0 predictive_accuracy 0 predictive_accuracy 0 predictive_accuracy 0 predictive_accuracy 0.00625 predictive_accuracy 0.00625 predictive_accuracy 0 predictive_accuracy 0 predictive_accuracy 0 predictive_accuracy 0 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5] recall 0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 0.9989172789725445 relative_absolute_error 0.9989149793918003 relative_absolute_error 0.9989649038121985 relative_absolute_error 0.9989630385051814 relative_absolute_error 0.9989974797431017 relative_absolute_error 0.998994907431976 relative_absolute_error 0.9989452639873337 relative_absolute_error 0.9989432946418428 relative_absolute_error 0.9989202249225161 relative_absolute_error 0.9989210416206453 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_squared_error 0.09946626295739336 root_mean_squared_error 0.09946599134948665 root_mean_squared_error 0.0994653996203572 root_mean_squared_error 0.09946521985915996 root_mean_squared_error 0.0994652449939405 root_mean_squared_error 0.09946498668967074 root_mean_squared_error 0.09946619077252973 root_mean_squared_error 0.09946597236231376 root_mean_squared_error 0.09946619139606336 root_mean_squared_error 0.09946629794726866 root_relative_squared_error 0.9996735561469684 root_relative_squared_error 0.9996708263847968 root_relative_squared_error 0.9996648792832821 root_relative_squared_error 0.9996630726152727 root_relative_squared_error 0.9996633252293218 root_relative_squared_error 0.9996607291737323 root_relative_squared_error 0.9996728306617922 root_relative_squared_error 0.9996706355565292 root_relative_squared_error 0.9996728369285409 root_relative_squared_error 0.9996739078084468 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 usercpu_time_millis 2862.4583079999866 usercpu_time_millis 2689.9752219997026 usercpu_time_millis 2695.210856999438 usercpu_time_millis 2699.352213000566 usercpu_time_millis 2687.5448769997092 usercpu_time_millis 2704.2730810007924 usercpu_time_millis 2705.671445999542 usercpu_time_millis 2692.4080879998655 usercpu_time_millis 2698.4559440006706 usercpu_time_millis 2709.039842000493 usercpu_time_millis_testing 153.862203999779 usercpu_time_millis_testing 153.96954599964374 usercpu_time_millis_testing 152.02980999947613 usercpu_time_millis_testing 154.63153000018792 usercpu_time_millis_testing 145.03131800029223 usercpu_time_millis_testing 146.59892800045782 usercpu_time_millis_testing 146.03801999965071 usercpu_time_millis_testing 146.87555599994084 usercpu_time_millis_testing 152.1323080005459 usercpu_time_millis_testing 152.6514600000155 usercpu_time_millis_training 2708.5961040002076 usercpu_time_millis_training 2536.005676000059 usercpu_time_millis_training 2543.181046999962 usercpu_time_millis_training 2544.720683000378 usercpu_time_millis_training 2542.513558999417 usercpu_time_millis_training 2557.6741530003346 usercpu_time_millis_training 2559.633425999891 usercpu_time_millis_training 2545.5325319999247 usercpu_time_millis_training 2546.3236360001247 usercpu_time_millis_training 2556.3883820004776