6050169 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) 4084822 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "median" 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 11266.533189881196 6953 cache_size 200 6953 class_weight null 6953 coef0 0.41650569736003296 6953 decision_function_shape null 6953 degree 5 6953 gamma 0.000833061229481192 6953 kernel "poly" 6953 max_iter -1 6953 probability true 6953 random_state 31554 6953 shrinking false 6953 tol 0.0045111538437499375 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 13023506 description https://api.openml.org/data/download/13023506/description.xml -1 13023507 predictions https://api.openml.org/data/download/13023507/predictions.arff area_under_roc_curve 0.8150276199494947 [0.433594,0.896859,0.763415,0.964212,0.807568,0.94117,0.915956,0.8619,0.945273,0.999763,0.913628,0.851089,0.847301,0.680674,0.819997,0.665404,0.898635,0.897175,0.90187,0.873856,0.92803,0.651712,0.755169,0.920021,0.914694,0.935014,0.834793,0.683594,0.72309,0.910985,0.855982,0.974945,0.858191,0.974787,0.721788,0.993766,0.930674,0.905737,0.929253,0.973445,0.557884,0.739347,0.973288,0.743292,0.914418,0.53342,0.931503,0.869949,0.631944,0.732955,0.580966,0.776081,0.671125,0.558002,0.705374,0.938684,0.999527,0.751618,0.937461,0.683594,0.852825,0.863873,0.978022,0.762705,0.887863,0.756471,0.843119,0.979206,0.706834,0.560646,0.771741,0.994594,0.831203,0.660432,0.753985,0.830729,0.772964,0.699298,0.786103,0.914457,0.663116,0.972814,0.729324,0.965791,0.63151,0.694484,0.944642,0.646228,0.625,0.82631,0.891177,0.971117,0.757221,0.793205,0.647964,0.81104,0.793363,0.910196,0.795415,0.740333] average_cost 0 kappa 0.09217171717171718 kb_relative_information_score 146.8552563540798 mean_absolute_error 0.01962964805831031 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 0.10125 prior_entropy 6.6438561897747395 recall 0.10125 [0,0,0.1875,0.25,0.1875,0.125,0.0625,0,0.25,0.8125,0.0625,0,0,0,0,0,0.125,0.0625,0.0625,0,0.125,0,0,0.0625,0.125,0.0625,0,0,0.0625,0.1875,0.0625,0.375,0,0.1875,0,1,0,0,0.25,0.3125,0,0.1875,0.3125,0,0.1875,0,0.1875,0,0,0,0,0,0,0,0.0625,0,1,0,0.125,0,0.25,0,0.25,0,0.25,0,0,0.3125,0,0,0,0.625,0,0,0,0.125,0.125,0,0.1875,0.0625,0,0.0625,0,0.0625,0,0,0.25,0,0,0,0.0625,0.375,0.0625,0,0,0,0,0,0,0] relative_absolute_error 0.991396366581327 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09878184220100925 root_relative_squared_error 0.9927948687298249 total_cost 0 area_under_roc_curve 0.9060870452193293 [0.805031,0.958861,0.939873,1,0.958861,1,0.987342,0.987421,0.993671,1,0.962025,0.914557,0.892405,0.905063,0.946203,0.748428,0.879747,0.936709,0.886076,0.886792,0.90566,0.874214,0.761006,0.968553,1,0.971519,0.886076,0.787975,0.981013,1,0.882911,0.993671,0.876582,0.977848,0.924051,0.987421,0.968553,0.918239,1,0.996835,0.792453,0.981132,1,0.943038,0.990506,0.610759,1,0.968553,0.746835,0.946203,0.655063,0.917722,0.886792,0.658228,0.974843,0.981132,1,0.987421,0.981132,0.914557,1,0.937107,0.993671,0.924051,0.981132,0.943038,0.879747,1,0.981132,0.515723,0.803797,1,0.873418,0.800633,0.981132,0.981013,0.990506,0.772152,0.984177,0.955696,0.756329,0.984177,0.987421,0.968553,0.689873,0.946203,0.981013,0.822785,0.734177,0.830189,0.943038,0.987421,0.987342,0.844937,0.762658,0.917722,0.792453,0.952532,0.879747,0.792453] area_under_roc_curve 0.906294283894594 [0.704403,0.987342,0.898734,1,0.981013,0.993711,0.993671,0.987421,0.987342,1,0.968354,0.962025,0.949367,0.582278,0.933544,0.773585,0.898734,0.949367,0.946203,0.867925,0.937107,0.786164,0.792453,0.987421,0.962264,0.943038,0.857595,0.955696,0.914557,1,0.905063,1,0.892405,0.993671,0.905063,0.987421,0.968553,0.899371,0.987421,1,0.72327,0.974843,1,0.920886,0.990506,0.705696,1,0.937107,0.800633,0.962025,0.674051,0.882911,0.930818,0.658228,0.943396,1,1,1,0.955975,0.85443,0.974843,0.855346,0.987342,0.898734,0.993711,0.901899,0.863924,0.993711,0.666667,0.836478,0.797468,1,0.863924,0.873418,0.91195,0.974684,0.958861,0.775316,0.987342,0.993671,0.860759,0.971519,0.993711,0.955975,0.686709,0.889241,0.996835,0.863924,0.791139,0.937107,0.968354,0.987421,0.987342,0.803797,0.851266,0.901899,0.823899,0.955696,0.803797,0.849057] area_under_roc_curve 0.9054272649470585 [0.436709,0.987342,0.943038,0.993711,0.981013,0.993671,0.943396,0.901899,0.971519,1,0.984177,0.962025,0.930818,0.851266,0.851266,0.797468,0.952532,0.889241,0.949686,0.962025,0.874214,0.716981,0.724684,0.981132,0.90566,0.968354,0.860759,0.830189,0.949367,0.977848,0.855346,1,0.870253,0.987342,0.899371,1,0.955975,0.855346,0.987421,0.990506,0.689873,0.974843,1,0.962264,0.984177,0.698113,0.996835,0.930818,0.740506,0.990506,0.800633,0.962264,0.930818,0.800633,0.987421,0.977848,1,0.981013,0.924528,0.898734,0.974843,0.930818,0.996835,0.823899,0.984177,0.936709,0.876582,1,0.974843,0.60443,0.860759,0.993671,0.893082,0.873418,0.880503,0.958861,0.974684,0.841772,0.933544,0.949367,0.987421,0.974684,0.987342,0.96519,0.761006,0.830189,1,0.765823,0.734177,0.899371,0.914557,0.987421,1,0.889241,0.664557,0.874214,0.911392,0.977848,0.930818,0.810127] area_under_roc_curve 0.906446292094578 [0.588608,0.968354,0.939873,1,0.933544,0.962025,0.981132,0.971519,0.974684,1,0.971519,0.939873,0.918239,0.693038,0.927215,0.791139,0.958861,0.920886,0.855346,0.905063,0.955975,0.861635,0.806962,0.993711,0.981132,0.952532,0.813291,0.81761,0.96519,0.958861,0.91195,1,0.879747,0.993671,0.943396,1,0.962264,0.886792,0.993711,1,0.727848,1,1,0.987421,0.987342,0.666667,0.996835,0.974843,0.848101,0.993671,0.870253,0.943396,0.823899,0.598101,0.962264,0.927215,1,0.93038,0.949686,0.943038,0.981132,0.943396,0.990506,0.924528,0.981013,0.917722,0.898734,0.981013,1,0.575949,0.813291,0.996835,0.836478,0.797468,0.811321,0.981013,0.977848,0.762658,0.987342,0.943038,0.842767,0.96519,0.987342,0.984177,0.955975,0.987421,0.987421,0.734177,0.746835,0.880503,0.873418,1,0.962264,0.870253,0.822785,0.861635,0.867089,0.974684,0.691824,0.927215] area_under_roc_curve 0.902867755353873 [0.436709,0.981132,0.844937,1,0.974843,0.996835,0.993711,0.933544,0.974843,1,0.968354,0.952532,0.918239,0.767296,0.937107,0.75,0.905063,0.917722,0.918239,0.860759,0.946203,0.759494,0.841772,0.993671,0.889241,0.955696,0.829114,0.930818,0.974843,0.898734,0.899371,1,0.813291,0.981013,0.867925,1,0.917722,0.914557,1,1,0.670886,0.996835,1,0.90566,0.993711,0.534591,1,0.968354,0.803797,0.984177,0.91195,0.962264,0.96519,0.867925,0.958861,0.984177,1,0.892405,0.962025,0.943396,0.987342,0.870253,0.987421,0.993711,0.984177,0.876582,0.880503,1,0.905063,0.636076,0.797468,1,0.842767,0.955975,0.797468,0.949686,0.96519,0.781646,0.971519,0.937107,0.930818,0.987342,0.936709,0.962025,0.735849,0.836478,0.981132,0.855346,0.731013,0.927215,0.842767,0.990506,1,0.893082,0.724684,0.861635,0.933544,0.993711,0.767296,0.718354] area_under_roc_curve 0.9008807021733938 [0.329114,0.993711,0.835443,1,1,0.96519,0.987421,0.955696,1,0.996835,0.974684,0.946203,0.899371,0.90566,0.937107,0.756329,0.898734,0.892405,0.899371,0.851266,0.949367,0.743671,0.841772,0.993671,0.876582,0.952532,0.813291,0.779874,0.987421,0.914557,0.899371,1,0.886076,0.990506,0.830189,0.996835,0.949367,0.914557,0.990506,0.993671,0.658228,0.984177,1,0.949686,0.987421,0.792453,1,0.898734,0.825949,0.984177,0.773585,0.974843,0.822785,0.754717,0.89557,0.955696,1,0.968354,0.968354,0.974843,0.901899,0.873418,0.987421,0.981132,0.996835,0.835443,0.830189,1,0.946203,0.594937,0.806962,0.993671,0.836478,0.874214,0.876582,0.886792,0.987342,0.708861,0.968354,0.924528,0.924528,0.993671,0.971519,0.958861,0.761006,0.962264,0.987421,0.886792,0.756329,0.93038,0.962264,0.990506,0.968553,0.943396,0.816456,0.899371,0.857595,0.987421,0.805031,0.765823] area_under_roc_curve 0.9018315619775492 [0.335443,0.962264,0.962264,1,1,1,0.987342,0.920886,0.993711,1,0.987421,0.968553,0.917722,0.981132,0.974843,0.693038,0.91195,0.899371,0.952532,0.857595,0.971519,0.803797,0.838608,0.968354,0.946203,0.867925,0.91195,0.778481,0.993711,0.987342,0.867089,0.993711,0.899371,0.968553,0.886076,1,0.955696,0.93038,0.996835,1,0.648734,0.990506,1,0.946203,0.918239,0.712025,0.990506,0.873418,0.893082,0.987421,0.767296,0.933544,0.797468,0.685535,0.876582,0.943038,1,0.863924,0.96519,0.987421,0.920886,0.829114,0.987421,0.974684,0.974684,0.918239,0.880503,0.987342,0.882911,0.664557,0.823899,1,0.867089,0.855346,0.838608,0.962264,0.993711,0.716981,0.955975,0.968553,0.867089,0.981132,0.977848,0.984177,0.737342,0.860759,0.993671,0.742138,0.861635,0.886076,0.943396,1,0.987342,0.830189,0.811321,0.927215,0.844937,0.949686,0.841772,0.813291] area_under_roc_curve 0.9076165810843081 [0.512658,0.955975,0.962264,1,1,0.993671,0.993671,0.949367,0.981132,1,0.943396,0.987421,0.914557,0.987421,0.874214,0.768987,0.918239,0.849057,0.927215,0.911392,0.955696,0.753165,0.794304,0.974684,0.968354,0.962264,0.886792,0.806962,0.842767,0.968354,0.867089,1,0.893082,0.987421,0.901899,1,0.943038,0.911392,0.993671,1,0.816456,0.993671,1,0.917722,0.968553,0.655063,1,0.939873,0.880503,0.955975,0.566038,0.860759,0.844937,0.710692,0.892405,0.952532,1,0.977848,0.955696,0.930818,0.955696,0.844937,0.987421,0.952532,0.990506,0.842767,0.830189,1,0.85443,0.797468,0.805031,1,0.867089,0.943396,0.867089,0.962264,1,0.861635,1,0.949686,0.813291,0.981132,0.968354,0.977848,0.71519,0.886076,0.993671,0.767296,0.792453,0.889241,0.962264,1,0.996835,0.930818,0.830189,0.879747,0.882911,0.962264,0.844937,0.787975] area_under_roc_curve 0.9063490167980255 [0.779874,0.952532,0.91195,1,0.993671,0.968553,0.984177,0.993711,0.974684,1,0.962264,0.981132,0.946203,0.81962,0.914557,0.773585,0.943396,0.90566,0.943038,0.886792,0.981013,0.708861,0.842767,0.962025,0.920886,0.981132,0.867925,0.892405,0.984177,1,0.908228,1,0.91195,0.987421,0.958861,1,0.952532,0.962025,0.990506,1,0.698113,0.993671,1,0.905063,0.977848,0.509494,1,0.936709,0.943396,0.981132,0.708861,0.873418,0.832278,0.579114,0.920886,0.886792,1,0.81761,0.984177,0.968354,0.971519,0.886076,0.996835,0.93038,0.987421,0.987421,0.851266,1,0.946203,0.610063,0.842767,0.987421,0.829114,0.946203,0.848101,0.905063,0.987421,0.81761,0.955975,0.949367,0.78481,0.962264,0.981132,0.981132,0.721519,0.740506,0.996835,0.689873,0.773585,0.879747,0.917722,0.990506,0.993671,0.873418,0.880503,0.832278,0.874214,0.993671,0.844937,0.842767] area_under_roc_curve 0.9051550931454502 [0.628931,0.93038,0.943396,0.993671,0.974684,1,0.993671,0.981132,0.981013,1,0.968553,0.981132,0.908228,0.835443,0.879747,0.710692,0.949686,0.974843,0.93038,0.874214,0.911392,0.693038,0.867925,0.971519,0.914557,0.987421,0.867925,0.822785,0.936709,0.981132,0.914557,1,0.836478,0.993711,0.939873,0.993671,0.962025,0.946203,0.996835,1,0.842767,0.993671,1,0.949367,0.96519,0.734177,1,0.958861,0.880503,0.987421,0.740506,0.911392,0.787975,0.677215,0.89557,0.955975,1,0.949686,0.96519,0.914557,0.958861,0.920886,0.984177,0.905063,0.981132,0.955975,0.867089,1,0.984177,0.823899,0.805031,1,0.924051,0.851266,0.743671,0.908228,0.993711,0.779874,0.981132,0.962025,0.829114,0.974843,0.937107,0.993711,0.702532,0.791139,0.996835,0.655063,0.861635,0.860759,0.876582,1,0.996835,0.81962,0.842767,0.863924,0.773585,0.943038,0.803797,0.811321] 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 0.08790690360119514 kappa 0.09423281047293314 kappa 0.1316317300507335 kappa 0.06885297471589791 kappa 0.07467149264300889 kappa 0.0873328088119591 kappa 0.1316658801321378 kappa 0.10663730732934885 kappa 0.08790690360119514 kappa 0.08147216105693614 kb_relative_information_score 14.31963364294071 kb_relative_information_score 14.03514125262044 kb_relative_information_score 14.947832766797706 kb_relative_information_score 14.536118496984955 kb_relative_information_score 14.752599015875438 kb_relative_information_score 14.678517018306298 kb_relative_information_score 15.494973392676613 kb_relative_information_score 15.334873554703854 kb_relative_information_score 14.32780287905705 kb_relative_information_score 14.427764334116864 mean_absolute_error 0.01962372552094 mean_absolute_error 0.019662487813822946 mean_absolute_error 0.019605740547970863 mean_absolute_error 0.01963154133008125 mean_absolute_error 0.019659255424173357 mean_absolute_error 0.019619821466542463 mean_absolute_error 0.01960243268084371 mean_absolute_error 0.019625770878064157 mean_absolute_error 0.01964288383079695 mean_absolute_error 0.019622821089867522 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 0.09375 predictive_accuracy 0.1 predictive_accuracy 0.1375 predictive_accuracy 0.075 predictive_accuracy 0.08125 predictive_accuracy 0.09375 predictive_accuracy 0.1375 predictive_accuracy 0.1125 predictive_accuracy 0.09375 predictive_accuracy 0.0875 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 0.09375 [0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.1 [0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.1375 [0,0,0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,1,1,0,0,0,1,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0.5,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.075 [0,0,0,1,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.08125 [0,0,0,0,1,0,0,0,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0.5,1,0,0,0,0,0,0,0] recall 0.09375 [0,0,0,0,1,0,0,0,1,0.5,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0.5,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0.5,0,0,0,0,0,0,0,0] recall 0.1375 [0,0,1,0,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,1,0,1,0,0,0,1,0,0,0.5,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0.5,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.1125 [0,0,1,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0.5,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.09375 [0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0875 [0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0.5,0,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 0.9910972485323216 relative_absolute_error 0.9930549400920664 relative_absolute_error 0.9901889165641833 relative_absolute_error 0.9914919863677383 relative_absolute_error 0.9928916880895617 relative_absolute_error 0.9909000740677996 relative_absolute_error 0.9900218525678625 relative_absolute_error 0.991200549397178 relative_absolute_error 0.9920648399392382 relative_absolute_error 0.9910515701953276 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 0.09878173899792227 root_mean_squared_error 0.09890205326829511 root_mean_squared_error 0.09867210040836727 root_mean_squared_error 0.09879534449478068 root_mean_squared_error 0.09888585018833965 root_mean_squared_error 0.09876650617761101 root_mean_squared_error 0.0986567453722126 root_mean_squared_error 0.09874103826070389 root_mean_squared_error 0.09883685310929827 root_mean_squared_error 0.09877989778532993 root_relative_squared_error 0.9927938314997745 root_relative_squared_error 0.9940030354141747 root_relative_squared_error 0.9916919222146299 root_relative_squared_error 0.9929305718881554 root_relative_squared_error 0.9938401883333856 root_relative_squared_error 0.9926407358953158 root_relative_squared_error 0.9915375982947288 root_relative_squared_error 0.9923847736996404 root_relative_squared_error 0.9933477491606475 root_relative_squared_error 0.9927753266169623 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 2097.4629169999994 usercpu_time_millis 1959.5423799999985 usercpu_time_millis 2002.0477679999988 usercpu_time_millis 2009.0155860000002 usercpu_time_millis 2023.5249970000027 usercpu_time_millis 2032.2054480000027 usercpu_time_millis 2030.0038580000007 usercpu_time_millis 2027.4509380000013 usercpu_time_millis 2028.046952999997 usercpu_time_millis 2042.8620449999996 usercpu_time_millis_testing 133.77621899999957 usercpu_time_millis_testing 141.82993999999917 usercpu_time_millis_testing 136.27645399999898 usercpu_time_millis_testing 142.70769800000062 usercpu_time_millis_testing 141.85700600000217 usercpu_time_millis_testing 142.42821500000247 usercpu_time_millis_testing 142.36405000000119 usercpu_time_millis_testing 150.76380500000042 usercpu_time_millis_testing 142.19150699999972 usercpu_time_millis_testing 142.31055500000167 usercpu_time_millis_training 1963.686698 usercpu_time_millis_training 1817.7124399999993 usercpu_time_millis_training 1865.7713139999998 usercpu_time_millis_training 1866.3078879999996 usercpu_time_millis_training 1881.6679910000005 usercpu_time_millis_training 1889.7772330000003 usercpu_time_millis_training 1887.6398079999994 usercpu_time_millis_training 1876.6871330000008 usercpu_time_millis_training 1885.8554459999973 usercpu_time_millis_training 1900.551489999998