6124377 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) 4158395 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 4575.042171095124 6953 cache_size 200 6953 class_weight null 6953 coef0 0.621239426986137 6953 decision_function_shape null 6953 degree 3 6953 gamma 5.656826792363555e-05 6953 kernel "sigmoid" 6953 max_iter -1 6953 probability true 6953 random_state 11245 6953 shrinking false 6953 tol 1.1285024520880145e-05 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 13174992 description https://api.openml.org/data/download/13174992/description.xml -1 13174993 predictions https://api.openml.org/data/download/13174993/predictions.arff area_under_roc_curve 0.33590909090909077 [0.419074,0.329545,0.342645,0.304845,0.316051,0.314986,0.312303,0.323193,0.313842,0.572759,0.321338,0.337279,0.347104,0.352115,0.322206,0.388139,0.316406,0.344736,0.341461,0.365333,0.327809,0.355508,0.354561,0.314749,0.329467,0.328835,0.383286,0.343158,0.314828,0.309935,0.333136,0.303662,0.359691,0.30958,0.345249,0.305911,0.331124,0.345328,0.312342,0.301807,0.391335,0.307528,0.301255,0.323035,0.307371,0.40696,0.303346,0.338502,0.33065,0.316367,0.353969,0.320312,0.329151,0.363518,0.319997,0.332741,0.301136,0.311237,0.320036,0.335859,0.307094,0.349511,0.307449,0.312737,0.306226,0.323311,0.37358,0.304727,0.334399,0.366753,0.366714,0.303188,0.348445,0.326271,0.361427,0.318813,0.309343,0.380682,0.307528,0.320904,0.348406,0.311948,0.311632,0.315301,0.373422,0.318458,0.303425,0.334991,0.339173,0.357599,0.340633,0.305516,0.308594,0.364031,0.359217,0.331795,0.356692,0.320628,0.395005,0.355705] average_cost 0 kappa -0.010101010101010102 kb_relative_information_score 13.746294721397481 mean_absolute_error 0.019797980792752214 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 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] relative_absolute_error 0.9998980198359686 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09949320764731 root_relative_squared_error 0.9999443604698349 total_cost 0 area_under_roc_curve 0.04735341533317412 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[0.079114,0.018987,0,0,0.003165,0.012658,0.044025,0.050633,0.022152,1,0.012658,0.015823,0.018868,0.025316,0.053797,0.117089,0.012658,0.107595,0.062893,0.041139,0.113208,0.056604,0.231013,0.012579,0.031447,0.041139,0.136076,0.056604,0.006329,0.022152,0.081761,0,0.110759,0.015823,0.044025,0,0.050314,0.144654,0.012579,0.009494,0.129747,0.025157,0,0.006289,0.006329,0.163522,0,0.069182,0.018987,0.009494,0.037975,0,0.006289,0.006329,0.012579,0.028481,0,0.006329,0.075472,0.060127,0.012579,0.062893,0.003165,0.062893,0.006329,0.044304,0.132911,0,0.012579,0.060127,0.066456,0.006329,0.012579,0.025316,0.044025,0.009494,0.012658,0.03481,0.028481,0.041139,0.025157,0.025316,0.006329,0.031646,0.08805,0.037736,0,0.015823,0.091772,0.075472,0.075949,0,0,0.075949,0.037975,0.062893,0.050633,0.022152,0.081761,0.037975] area_under_roc_curve 0.05717374213836481 [0.234177,0.028481,0,0,0.006329,0.03481,0.012579,0.015823,0.022152,1,0.018987,0.022152,0.056604,0.085443,0.022152,0.117089,0.009494,0.082278,0.150943,0.091772,0.025157,0.012579,0.044304,0.006289,0.025157,0.047468,0.18038,0.044025,0.006329,0.009494,0.025157,0,0.091772,0.006329,0.031447,0,0.044025,0.119497,0.006289,0,0.063291,0,0,0.006289,0,0.08805,0.006329,0.025157,0,0.006329,0.025316,0.006289,0.018868,0.14557,0.012579,0.072785,0,0.003165,0.044025,0.037975,0.018868,0.037736,0.006329,0.018868,0.006329,0.022152,0.101266,0.012658,0,0.161392,0.161392,0.006329,0.138365,0.037975,0.044025,0.006329,0.006329,0.14557,0,0.050633,0.113208,0.03481,0.009494,0.015823,0.006289,0.025157,0,0.031646,0.041139,0.081761,0.10443,0,0.025157,0.075949,0.015823,0.069182,0.120253,0.025316,0.308176,0.012658] area_under_roc_curve 0.05834602141549246 [0.107595,0.018868,0.012658,0,0.018868,0.006329,0,0.037975,0.025157,1,0.022152,0.015823,0.062893,0.220126,0.025157,0.183544,0.015823,0.063291,0.069182,0.132911,0.025316,0.044304,0,0.006329,0.072785,0.041139,0.177215,0,0.018868,0.028481,0.044025,0,0.161392,0.018987,0.062893,0,0.06962,0.098101,0,0,0.189873,0,0,0.012579,0,0.251572,0,0.018987,0,0.009494,0.031447,0.044025,0.006329,0.018868,0.009494,0.015823,0,0.028481,0.028481,0.037736,0,0.063291,0.012579,0,0.003165,0.022152,0.119497,0,0.037975,0.060127,0.10443,0,0.044025,0.031447,0.14557,0.018868,0.022152,0.123418,0.006329,0.056604,0.044025,0.012658,0.006329,0.037975,0.150943,0.031447,0.018868,0.012579,0.03481,0.056962,0.132075,0.009494,0,0.09434,0.063291,0.050314,0.041139,0,0.232704,0.161392] area_under_roc_curve 0.06053906934161294 [0.227848,0,0.015823,0,0,0.03481,0.006289,0.012658,0,0.993671,0.018987,0.025316,0.069182,0.037736,0.031447,0.164557,0.031646,0.094937,0.08805,0.14557,0.031646,0.063291,0.006329,0,0.053797,0.047468,0.193038,0.106918,0.006289,0.018987,0.037736,0,0.091772,0.009494,0.037736,0.003165,0.053797,0.082278,0.006329,0,0.186709,0.012658,0,0.025157,0.006289,0.125786,0,0.050633,0.018987,0.015823,0.012579,0.012579,0.041139,0.056604,0.053797,0.047468,0,0.006329,0.031646,0.018868,0.018987,0.088608,0.012579,0,0,0.056962,0.138365,0,0.015823,0.047468,0.123418,0.006329,0.08805,0.031447,0.044304,0.037736,0.012658,0.243671,0.003165,0.069182,0.075472,0,0.012658,0.041139,0.08805,0.012579,0,0.006289,0.066456,0.053797,0.050314,0.006329,0.018868,0.044025,0.03481,0.012579,0.129747,0.018868,0.188679,0.158228] area_under_roc_curve 0.05842488655361838 [0.088608,0.037736,0,0,0,0.003165,0.006329,0.025316,0.006289,1,0.006289,0.006289,0.056962,0.012579,0,0.221519,0.044025,0.106918,0.047468,0.14557,0.022152,0.025316,0.028481,0.015823,0.022152,0.144654,0.081761,0.113924,0,0.003165,0.085443,0.006289,0.113208,0.031447,0.022152,0,0.041139,0.075949,0.003165,0,0.177215,0.006329,0,0.012658,0.075472,0.066456,0.009494,0.079114,0.018868,0.012579,0.113208,0.009494,0.031646,0.119497,0.056962,0.060127,0,0.006329,0.03481,0.012579,0.022152,0.136076,0.012579,0,0.012658,0.062893,0.132075,0.006329,0.044304,0.03481,0.125786,0,0.075949,0.056604,0.03481,0.012579,0,0.257862,0.006289,0.025157,0.139241,0.018868,0.012658,0.012658,0.056962,0.012658,0,0.044025,0.050314,0.075949,0.044025,0,0.012658,0.138365,0.031447,0.015823,0.129747,0.050314,0.158228,0.066456] area_under_roc_curve 0.05581462463179685 [0.053797,0.031447,0,0,0,0.006329,0.009494,0.015823,0.018868,1,0.050314,0,0.050633,0.006289,0.062893,0.139241,0.025157,0.144654,0.06962,0.075949,0.025316,0.028481,0.129747,0.015823,0.025316,0.037736,0.132075,0.03481,0.150943,0.006329,0.063291,0,0.08805,0.012579,0.018987,0,0.056962,0.094937,0.003165,0,0.158228,0.003165,0,0.022152,0.025157,0.132911,0,0.050633,0.012579,0.044025,0.283019,0.03481,0.050633,0.062893,0.018987,0.047468,0,0,0.044304,0.056604,0.003165,0.113924,0.012579,0.006329,0.003165,0.08805,0.176101,0,0.03481,0.022152,0.132075,0,0.075949,0.018868,0.044304,0.018868,0,0.031447,0,0.031447,0.085443,0.018868,0.015823,0.022152,0.050633,0.028481,0,0.025157,0.069182,0.06962,0.037736,0,0.003165,0.037736,0.025157,0.028481,0.072785,0.037736,0.14557,0.148734] area_under_roc_curve 0.041971678210333596 [0.075472,0.031646,0.012579,0,0,0.018868,0.012658,0,0.012658,0,0.025157,0.006289,0.015823,0.056962,0.018987,0.176101,0.006289,0.09434,0.060127,0.119497,0.015823,0.018987,0.100629,0.015823,0.044304,0.018868,0.125786,0.012658,0,0.012579,0.044304,0,0.075472,0.012579,0.009494,0,0.047468,0.044304,0.006329,0,0.207547,0,0,0.028481,0.012658,0.25,0,0.031646,0.025157,0.018868,0.088608,0.009494,0.015823,0.142405,0.044304,0.125786,0,0.031447,0.012658,0.025316,0.006329,0.091772,0.003165,0.009494,0.006289,0.018868,0.14557,0,0.018987,0.119497,0.056604,0.012579,0.161392,0.022152,0.031646,0.047468,0,0.119497,0.018868,0.047468,0.094937,0.037736,0.006289,0.018868,0.028481,0.009494,0,0.025316,0.069182,0.094937,0.06962,0.009494,0.006329,0.088608,0.025157,0.082278,0.081761,0.006329,0.148734,0.075472] area_under_roc_curve 0.040788452352519725 [0.18239,0.056962,0,0,0,0,0.003165,0,0.018987,0,0.025157,0.012579,0.031646,0.03481,0.022152,0.232704,0.018868,0.025157,0.06962,0.132075,0.06962,0.066456,0,0.015823,0.044304,0.012579,0.119497,0.053797,0.018987,0.044025,0.028481,0,0.132075,0,0.028481,0.009494,0.03481,0.050633,0,0,0.050314,0.006329,0,0.015823,0.015823,0.041139,0,0.041139,0.018868,0.012579,0.050633,0.009494,0.031646,0.091772,0.009494,0.037736,0,0.012579,0.031646,0.056962,0.012658,0.050633,0.015823,0.009494,0.018868,0.037736,0.129747,0,0,0.037736,0.163522,0,0.037975,0.041139,0.126582,0.03481,0,0.188679,0,0.025316,0.050633,0.025157,0.050314,0.006289,0.056962,0.009494,0.003165,0.044304,0.018868,0.113924,0.088608,0,0.006329,0.120253,0.018868,0.044304,0.169811,0.044304,0.202532,0.062893] 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 -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kappa -0.012658227848101266 kb_relative_information_score 1.4016064674083648 kb_relative_information_score 1.4019145143353626 kb_relative_information_score 1.3434814797557904 kb_relative_information_score 1.3525117032263325 kb_relative_information_score 1.3039034559293596 kb_relative_information_score 1.3141518597428117 kb_relative_information_score 1.4020201613118675 kb_relative_information_score 1.4073599133713603 kb_relative_information_score 1.406281087062231 kb_relative_information_score 1.4130640792540057 mean_absolute_error 0.01979808007659585 mean_absolute_error 0.019797984672842286 mean_absolute_error 0.01979804461085434 mean_absolute_error 0.019798010829662902 mean_absolute_error 0.019798085759766673 mean_absolute_error 0.01979801674977299 mean_absolute_error 0.019797878810474602 mean_absolute_error 0.01979780877753897 mean_absolute_error 0.019797920221760808 mean_absolute_error 0.019797977418252392 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 predictive_accuracy 0 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 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] 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 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] 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 0.9999030341715058 relative_absolute_error 0.9998982158001138 relative_absolute_error 0.9999012429724397 relative_absolute_error 0.99989953685166 relative_absolute_error 0.9999033212003353 relative_absolute_error 0.999899835847119 relative_absolute_error 0.9998928692158874 relative_absolute_error 0.9998893321989363 relative_absolute_error 0.9998949606949885 relative_absolute_error 0.9998978494066848 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 0.09949382913060993 root_mean_squared_error 0.09949332292468183 root_mean_squared_error 0.09949333420910388 root_mean_squared_error 0.0994931671854713 root_mean_squared_error 0.09949350926132368 root_mean_squared_error 0.09949314848681129 root_mean_squared_error 0.09949284578801086 root_mean_squared_error 0.09949247867552703 root_mean_squared_error 0.09949307154384693 root_mean_squared_error 0.09949336926158905 root_relative_squared_error 0.9999506066120151 root_relative_squared_error 0.9999455190510145 root_relative_squared_error 0.999945632463723 root_relative_squared_error 0.9999439538130556 root_relative_squared_error 0.9999473918047288 root_relative_squared_error 0.9999437658844513 root_relative_squared_error 0.9999407236470407 root_relative_squared_error 0.9999370340277537 root_relative_squared_error 0.9999429925785634 root_relative_squared_error 0.9999459847544544 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 3000.9005700000557 usercpu_time_millis 2707.450066999968 usercpu_time_millis 2694.352603000027 usercpu_time_millis 2693.0473909999932 usercpu_time_millis 2685.8926179999685 usercpu_time_millis 2695.381209000004 usercpu_time_millis 2722.4013169999353 usercpu_time_millis 2684.806855999966 usercpu_time_millis 2706.909345999975 usercpu_time_millis 2695.6695479999553 usercpu_time_millis_testing 156.37564400003612 usercpu_time_millis_testing 151.8995199999722 usercpu_time_millis_testing 158.18967300003806 usercpu_time_millis_testing 150.06908399999475 usercpu_time_millis_testing 144.96722799998452 usercpu_time_millis_testing 147.44272799998726 usercpu_time_millis_testing 148.63257099995053 usercpu_time_millis_testing 147.12639999999055 usercpu_time_millis_testing 149.18564999999262 usercpu_time_millis_testing 148.87414999998327 usercpu_time_millis_training 2844.5249260000196 usercpu_time_millis_training 2555.5505469999957 usercpu_time_millis_training 2536.162929999989 usercpu_time_millis_training 2542.9783069999985 usercpu_time_millis_training 2540.925389999984 usercpu_time_millis_training 2547.938481000017 usercpu_time_millis_training 2573.7687459999847 usercpu_time_millis_training 2537.6804559999755 usercpu_time_millis_training 2557.7236959999823 usercpu_time_millis_training 2546.795397999972