10591664 32426 Lucas Maertens 6 Supervised Classification 19096 sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer.ColumnTransformer(categorical=sklearn.preprocessing._encoders.OneHotEncoder,continuous=sklearn.impute._base.SimpleImputer),Classifier=sklearn.ensemble._forest.RandomForestClassifier)(2) 8304430 Python_3.7.13. Sklearn_1.0.2. NumPy_1.21.5. SciPy_1.7.3. add_indicator false 19084 copy true 19084 fill_value null 19084 missing_values NaN 19084 strategy "median" 19084 verbose 0 19084 bootstrap true 19095 ccp_alpha 0.0 19095 class_weight null 19095 criterion "gini" 19095 max_depth null 19095 max_features "auto" 19095 max_leaf_nodes null 19095 max_samples null 19095 min_impurity_decrease 0.0 19095 min_samples_leaf 1 19095 min_samples_split 2 19095 min_weight_fraction_leaf 0.0 19095 n_estimators 10 19095 n_jobs null 19095 oob_score false 19095 random_state 39373 19095 verbose 0 19095 warm_start false 19095 memory null 19096 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "Preprocessing", "step_name": "Preprocessing"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "Classifier", "step_name": "Classifier"}}] 19096 verbose false 19096 n_jobs null 19097 remainder "drop" 19097 sparse_threshold 0.3 19097 transformer_weights null 19097 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "categorical", "step_name": "categorical", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "continuous", "step_name": "continuous", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7]}}] 19097 verbose false 19097 verbose_feature_names_out true 19097 categories "auto" 19098 drop null 19098 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 19098 handle_unknown "ignore" 19098 sparse false 19098 openml-python Sklearn_1.0.2. 6 letter https://www.openml.org/data/download/6/dataset_6_letter.arff -1 22110935 description https://api.openml.org/data/download/22110935/description.xml -1 22110936 predictions https://api.openml.org/data/download/22110936/predictions.arff area_under_roc_curve 0.9199867222089111 [0.965415,0.876135,0.929734,0.879379,0.85832,0.935136,0.889859,0.846984,0.97123,0.951133,0.904089,0.957864,0.943628,0.872749,0.930008,0.91306,0.962353,0.858585,0.875476,0.935949,0.930535,0.952687,0.95298,0.94684,0.955098,0.919796] average_cost 0 f_measure 0.6345007335480467 [0.801714,0.4759,0.65623,0.518562,0.449652,0.618897,0.564356,0.456903,0.865333,0.757823,0.561995,0.806366,0.692208,0.54153,0.606258,0.602516,0.716749,0.452138,0.493267,0.695762,0.687147,0.714286,0.735836,0.665362,0.733068,0.613999] kappa 0.6193437454450118 kb_relative_information_score 0.6781757081290799 mean_absolute_error 0.03653307815148945 mean_prior_absolute_error 0.07396191835229461 weighted_recall 0.634 [0.830165,0.509138,0.683424,0.546584,0.46224,0.629677,0.589909,0.444142,0.859603,0.745649,0.564276,0.798949,0.67298,0.528736,0.61753,0.596513,0.743295,0.439314,0.465241,0.690955,0.674047,0.706806,0.716755,0.64803,0.70229,0.603542] number_of_instances 20000 [789,766,736,805,768,775,773,734,755,747,739,761,792,783,753,803,783,758,748,796,813,764,752,787,786,734] precision 0.6361479314441942 [0.775148,0.446735,0.631117,0.493274,0.437731,0.608479,0.540925,0.470418,0.871141,0.770401,0.559732,0.813922,0.712567,0.55496,0.595391,0.60864,0.692033,0.465734,0.524887,0.700637,0.700767,0.721925,0.755961,0.683646,0.766667,0.624824] predictive_accuracy 0.634 prior_entropy 4.6998107276322685 relative_absolute_error 0.4939444374262372 root_mean_prior_squared_error 0.19230433563020993 root_mean_squared_error 0.13915699169769838 root_relative_squared_error 0.7236289875714981 total_cost 0 unweighted_recall 0.6334534505249217 [0.830165,0.509138,0.683424,0.546584,0.46224,0.629677,0.589909,0.444142,0.859603,0.745649,0.564276,0.798949,0.67298,0.528736,0.61753,0.596513,0.743295,0.439314,0.465241,0.690955,0.674047,0.706806,0.716755,0.64803,0.70229,0.603542] area_under_roc_curve 0.9230906411044421 [0.949512,0.884045,0.930264,0.836537,0.847647,0.96216,0.883873,0.885765,0.954809,0.956018,0.895832,0.990159,0.950491,0.872272,0.921576,0.93512,0.979845,0.864557,0.885901,0.936083,0.934977,0.936216,0.97057,0.975566,0.965007,0.893379] area_under_roc_curve 0.9182441391145233 [0.954121,0.877251,0.928023,0.849475,0.840624,0.934049,0.941879,0.845391,0.980636,0.955295,0.899989,0.945601,0.924904,0.901271,0.954691,0.872308,0.961722,0.873906,0.885759,0.929974,0.946844,0.964892,0.908007,0.93433,0.942076,0.920964] area_under_roc_curve 0.9183340757437238 [0.967768,0.874263,0.948216,0.875774,0.84112,0.932759,0.894264,0.842391,0.957969,0.97063,0.952945,0.954594,0.915761,0.84796,0.913759,0.92457,0.950149,0.830401,0.886535,0.936495,0.960377,0.965918,0.953659,0.935694,0.944428,0.894562] area_under_roc_curve 0.9213425127054534 [0.975118,0.872956,0.904521,0.895879,0.874337,0.959564,0.907706,0.836754,0.976721,0.95218,0.922372,0.976256,0.956758,0.855771,0.942272,0.925384,0.939413,0.81396,0.850569,0.914364,0.966572,0.975883,0.920842,0.933417,0.966684,0.927258] area_under_roc_curve 0.9248899372139626 [0.990913,0.850393,0.916049,0.919463,0.867202,0.938232,0.888678,0.845572,0.977059,0.958847,0.887784,0.95618,0.926689,0.86899,0.942556,0.937497,0.97611,0.874053,0.899969,0.916221,0.938021,0.953547,0.972048,0.934238,0.961108,0.944296] area_under_roc_curve 0.9185178884114356 [0.94312,0.906954,0.94228,0.882357,0.861509,0.923377,0.86919,0.813583,0.983273,0.9105,0.885511,0.953424,0.933536,0.885506,0.95074,0.898695,0.968417,0.842396,0.85662,0.937266,0.934148,0.949403,0.979266,0.983098,0.968819,0.910835] area_under_roc_curve 0.917805672822234 [0.981504,0.838624,0.905631,0.852891,0.83,0.942928,0.88676,0.896207,0.970448,0.936997,0.873604,0.948203,0.947156,0.882518,0.914015,0.908975,0.965705,0.876905,0.887983,0.957988,0.921435,0.955363,0.963505,0.958612,0.957149,0.895458] area_under_roc_curve 0.9190776725475784 [0.976298,0.882977,0.960493,0.910622,0.845574,0.951898,0.884919,0.827538,0.977745,0.943487,0.901788,0.94797,0.9366,0.847308,0.90798,0.894438,0.96081,0.866865,0.899796,0.950417,0.915391,0.922872,0.953881,0.951838,0.936304,0.93869] area_under_roc_curve 0.9197584037769979 [0.941776,0.87936,0.937908,0.87691,0.903577,0.86136,0.91473,0.85078,0.97751,0.969157,0.902574,0.958594,0.975945,0.858511,0.90861,0.905207,0.96486,0.88098,0.852405,0.938594,0.93897,0.93381,0.955852,0.927526,0.972964,0.920428] area_under_roc_curve 0.9188677138151555 [0.974268,0.89476,0.923751,0.894695,0.871366,0.94533,0.826799,0.826268,0.95645,0.958431,0.91874,0.946907,0.967982,0.908252,0.944651,0.927547,0.956382,0.864104,0.849853,0.94279,0.849656,0.968398,0.952077,0.93381,0.935925,0.951255] 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 0.6385505652888724 [0.754717,0.454545,0.625767,0.521212,0.402778,0.611765,0.544304,0.513158,0.797203,0.739726,0.588235,0.849673,0.771242,0.540541,0.569444,0.6375,0.705128,0.467066,0.565517,0.697987,0.735484,0.734694,0.743243,0.70303,0.741722,0.569231] f_measure 0.6201472028770156 [0.807453,0.503067,0.670732,0.497041,0.433121,0.596273,0.621118,0.426471,0.818182,0.736111,0.56,0.761905,0.632911,0.549708,0.590604,0.558442,0.727273,0.421769,0.496241,0.700637,0.731707,0.688742,0.728571,0.573333,0.731034,0.550336] f_measure 0.6412657461972868 [0.8,0.484848,0.731034,0.503067,0.376623,0.696296,0.556962,0.481013,0.900662,0.74026,0.66242,0.821918,0.643357,0.531469,0.5875,0.68323,0.691358,0.414286,0.489796,0.698795,0.670588,0.774194,0.717949,0.726027,0.701299,0.575342] f_measure 0.65226105091792 [0.790698,0.457831,0.653061,0.545455,0.494253,0.710843,0.601156,0.4,0.881119,0.818792,0.528571,0.845638,0.717949,0.554054,0.6375,0.636943,0.724832,0.435374,0.496454,0.658385,0.792683,0.697368,0.711111,0.634483,0.832215,0.671053] f_measure 0.6301592995148407 [0.853659,0.466258,0.647059,0.552941,0.476821,0.601307,0.538922,0.460432,0.855346,0.675862,0.57931,0.84,0.64557,0.554054,0.559006,0.66242,0.678788,0.474074,0.481203,0.654545,0.662921,0.684932,0.782051,0.670886,0.727273,0.580645] f_measure 0.6511676817608665 [0.785714,0.5,0.641026,0.571429,0.493976,0.618182,0.545455,0.482759,0.893617,0.765101,0.543046,0.797386,0.675676,0.56338,0.68323,0.62963,0.770115,0.481203,0.427481,0.702703,0.696203,0.753086,0.813793,0.715152,0.693333,0.675862] f_measure 0.6180956549935586 [0.795031,0.3625,0.558442,0.434783,0.509317,0.622754,0.613497,0.486111,0.897959,0.763889,0.479452,0.805195,0.679739,0.541935,0.549296,0.564103,0.745342,0.435374,0.48,0.745342,0.61039,0.680556,0.743243,0.649682,0.710526,0.592593] f_measure 0.6270880222728189 [0.834356,0.5625,0.658824,0.513966,0.306569,0.571429,0.49697,0.485714,0.869565,0.758621,0.541353,0.808219,0.726115,0.51497,0.657895,0.509317,0.691358,0.513158,0.493151,0.705882,0.684564,0.723684,0.681481,0.636943,0.709677,0.647887] f_measure 0.6260564627847265 [0.823529,0.47561,0.680272,0.454545,0.425287,0.503497,0.585987,0.4,0.877419,0.772414,0.545455,0.780822,0.751592,0.5125,0.527778,0.537143,0.725,0.465409,0.5,0.716981,0.720497,0.685315,0.74026,0.684932,0.748387,0.619718] f_measure 0.6367214755420907 [0.77381,0.493976,0.701987,0.606061,0.546584,0.653846,0.536913,0.42029,0.863014,0.805369,0.580645,0.756098,0.675159,0.557823,0.68323,0.612245,0.705882,0.410959,0.496644,0.679012,0.549296,0.7125,0.689189,0.652778,0.736842,0.653061] kappa 0.6219542158995032 kappa 0.6052991834789367 kappa 0.6266388500476582 kappa 0.6370228384398015 kappa 0.6167311168569664 kappa 0.6385837579540824 kappa 0.6011348156522603 kappa 0.6131033170150297 kappa 0.608932155969505 kappa 0.6240431429993245 kb_relative_information_score 0.6852884833219534 kb_relative_information_score 0.6685976423762524 kb_relative_information_score 0.6825511713791534 kb_relative_information_score 0.6836499287340907 kb_relative_information_score 0.6845018988739856 kb_relative_information_score 0.6812793438536334 kb_relative_information_score 0.6700040026644113 kb_relative_information_score 0.6764076352261292 kb_relative_information_score 0.6738150204016294 kb_relative_information_score 0.6756619314440723 mean_absolute_error 0.035938829808327064 mean_absolute_error 0.0373827624472429 mean_absolute_error 0.035965757501360544 mean_absolute_error 0.036002432126367015 mean_absolute_error 0.03597664641322791 mean_absolute_error 0.03597924928703843 mean_absolute_error 0.03728606708040812 mean_absolute_error 0.036736634087067364 mean_absolute_error 0.037224032453846465 mean_absolute_error 0.03683837030996511 mean_prior_absolute_error 0.07396194754511427 mean_prior_absolute_error 0.07396200900367966 mean_prior_absolute_error 0.07396191681583157 mean_prior_absolute_error 0.07396192641873242 mean_prior_absolute_error 0.07396195714801512 mean_prior_absolute_error 0.07396196483033579 mean_prior_absolute_error 0.07396196867149613 mean_prior_absolute_error 0.07396191489525139 mean_prior_absolute_error 0.07396179389870075 mean_prior_absolute_error 0.0739617842957999 number_of_instances 2000 [79,77,74,81,77,77,77,73,76,74,74,76,79,78,75,80,78,76,75,79,82,77,75,78,79,74] number_of_instances 2000 [78,77,74,81,77,77,77,73,76,74,74,76,79,79,75,80,78,76,75,79,81,77,75,79,79,74] number_of_instances 2000 [79,77,74,81,76,78,77,73,76,74,74,76,79,79,75,80,78,76,74,79,81,77,75,79,79,74] number_of_instances 2000 [79,77,74,80,76,78,77,73,76,75,73,76,80,79,75,80,78,76,74,79,81,77,75,79,79,74] number_of_instances 2000 [79,77,74,80,77,78,77,73,76,75,74,76,80,78,75,80,78,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,74,80,77,78,78,73,75,75,74,76,79,78,76,80,79,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,73,80,77,78,78,74,75,75,74,76,79,78,76,80,79,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,73,80,77,77,78,74,75,75,74,76,79,78,76,81,79,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,73,81,77,77,77,74,75,75,74,77,79,78,75,81,78,75,75,80,82,76,76,78,79,73] number_of_instances 2000 [79,77,73,81,77,77,77,74,75,75,74,76,79,78,75,81,78,75,75,80,82,76,76,78,79,73] precision 0.6447856924780825 [0.75,0.40404,0.573034,0.511905,0.432836,0.55914,0.530864,0.493671,0.850746,0.75,0.56962,0.844156,0.797297,0.571429,0.594203,0.6375,0.705128,0.428571,0.585714,0.742857,0.780822,0.771429,0.753425,0.666667,0.777778,0.660714] precision 0.6230639218291145 [0.783133,0.476744,0.611111,0.477273,0.425,0.571429,0.595238,0.460317,0.807692,0.757143,0.552632,0.788732,0.632911,0.51087,0.594595,0.581081,0.689655,0.43662,0.568966,0.705128,0.722892,0.702703,0.784615,0.605634,0.80303,0.546667] precision 0.6460562951645019 [0.767442,0.454545,0.746479,0.5,0.371795,0.824561,0.54321,0.447059,0.906667,0.7125,0.626506,0.857143,0.71875,0.59375,0.552941,0.679012,0.666667,0.453125,0.493151,0.666667,0.640449,0.769231,0.691358,0.791045,0.72,0.583333] precision 0.6580471597012306 [0.731183,0.426966,0.657534,0.529412,0.438776,0.670455,0.541667,0.41791,0.940299,0.824324,0.552239,0.863014,0.736842,0.594203,0.6,0.649351,0.760563,0.450704,0.522388,0.646341,0.783133,0.706667,0.8,0.69697,0.885714,0.653846] precision 0.6331008252045576 [0.823529,0.44186,0.709677,0.522222,0.486486,0.613333,0.5,0.484848,0.819277,0.7,0.591549,0.851351,0.653846,0.585714,0.523256,0.675325,0.643678,0.542373,0.551724,0.635294,0.608247,0.714286,0.753086,0.670886,0.8,0.54878] precision 0.6546823578363231 [0.741573,0.4875,0.609756,0.567901,0.460674,0.586207,0.517241,0.486111,0.954545,0.77027,0.532468,0.792208,0.724638,0.625,0.647059,0.621951,0.705263,0.561404,0.5,0.764706,0.714286,0.709302,0.842857,0.686047,0.722222,0.680556] precision 0.6220330212973679 [0.780488,0.345238,0.530864,0.384615,0.488095,0.58427,0.588235,0.5,0.916667,0.797101,0.486111,0.794872,0.702703,0.545455,0.590909,0.578947,0.731707,0.450704,0.48,0.740741,0.643836,0.720588,0.753425,0.653846,0.72973,0.645161] precision 0.6309360390178221 [0.809524,0.535714,0.57732,0.464646,0.35,0.547619,0.471264,0.515152,0.813953,0.785714,0.610169,0.842857,0.730769,0.483146,0.657895,0.5125,0.674699,0.513158,0.507042,0.739726,0.75,0.723684,0.766667,0.641026,0.714286,0.666667] precision 0.6313926572201346 [0.851351,0.443182,0.675676,0.421053,0.381443,0.545455,0.575,0.442623,0.85,0.8,0.525,0.826087,0.75641,0.5,0.550725,0.5,0.707317,0.440476,0.557377,0.721519,0.734177,0.731343,0.730769,0.735294,0.763158,0.637681] precision 0.6392477678517653 [0.730337,0.460674,0.679487,0.595238,0.52381,0.64557,0.555556,0.453125,0.887324,0.810811,0.555556,0.704545,0.679487,0.594203,0.639535,0.681818,0.652174,0.422535,0.5,0.670732,0.65,0.678571,0.708333,0.712121,0.767123,0.648649] predictive_accuracy 0.6365 predictive_accuracy 0.6204999999999999 predictive_accuracy 0.6409999999999999 predictive_accuracy 0.6509999999999999 predictive_accuracy 0.6315 predictive_accuracy 0.6525 predictive_accuracy 0.6164999999999999 predictive_accuracy 0.628 predictive_accuracy 0.624 predictive_accuracy 0.6385000000000001 prior_entropy 4.699825815607033 prior_entropy 4.699854731688913 prior_entropy 4.699809751694497 prior_entropy 4.699813724681224 prior_entropy 4.6998289081692235 prior_entropy 4.699832499136173 prior_entropy 4.69983445932086 prior_entropy 4.699808889896364 prior_entropy 4.69975160696033 prior_entropy 4.699746889170326 relative_absolute_error 0.48590972792334325 relative_absolute_error 0.5054319501432564 relative_absolute_error 0.4862740049168393 relative_absolute_error 0.4867697999446461 relative_absolute_error 0.4864209628908312 relative_absolute_error 0.48645610442573584 relative_absolute_error 0.5041248597101989 relative_absolute_error 0.4966966328426683 relative_absolute_error 0.5032873121605067 relative_absolute_error 0.4980730340771007 root_mean_prior_squared_error 0.1923044115328483 root_mean_prior_squared_error 0.19230457132777806 root_mean_prior_squared_error 0.19230433163533361 root_mean_prior_squared_error 0.19230435660331052 root_mean_prior_squared_error 0.19230443650081483 root_mean_prior_squared_error 0.19230445647518574 root_mean_prior_squared_error 0.1923044664623704 root_mean_prior_squared_error 0.19230432664173788 root_mean_prior_squared_error 0.192304012044943 root_mean_prior_squared_error 0.19230398707692134 root_mean_squared_error 0.13746124001089471 root_mean_squared_error 0.14168507461174756 root_mean_squared_error 0.13834198439595738 root_mean_squared_error 0.13757024324480713 root_mean_squared_error 0.1381230041775206 root_mean_squared_error 0.1374707207793296 root_mean_squared_error 0.14086125435776817 root_mean_squared_error 0.13986609340336537 root_mean_squared_error 0.14060597974781622 root_mean_squared_error 0.139505312009281 root_relative_squared_error 0.7148106427470823 root_relative_squared_error 0.7367743451623368 root_relative_squared_error 0.7193908905717998 root_relative_squared_error 0.715377673572887 root_relative_squared_error 0.7182517818663813 root_relative_squared_error 0.7148597765183269 root_relative_squared_error 0.7324908097510648 root_relative_squared_error 0.7273164147987959 root_relative_squared_error 0.7311650872627424 root_relative_squared_error 0.7254415996766571 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 0.635998941717092 [0.759494,0.519481,0.689189,0.530864,0.376623,0.675325,0.558442,0.534247,0.75,0.72973,0.608108,0.855263,0.746835,0.512821,0.546667,0.6375,0.705128,0.513158,0.546667,0.658228,0.695122,0.701299,0.733333,0.74359,0.708861,0.5] unweighted_recall 0.619974385479887 [0.833333,0.532468,0.743243,0.518519,0.441558,0.623377,0.649351,0.39726,0.828947,0.716216,0.567568,0.736842,0.632911,0.594937,0.586667,0.5375,0.769231,0.407895,0.44,0.696203,0.740741,0.675325,0.68,0.544304,0.670886,0.554054] unweighted_recall 0.6407636134168905 [0.835443,0.519481,0.716216,0.506173,0.381579,0.602564,0.571429,0.520548,0.894737,0.77027,0.702703,0.789474,0.582278,0.481013,0.626667,0.6875,0.717949,0.381579,0.486486,0.734177,0.703704,0.779221,0.746667,0.670886,0.683544,0.567568] unweighted_recall 0.649724746377082 [0.860759,0.493506,0.648649,0.5625,0.565789,0.75641,0.675325,0.383562,0.828947,0.813333,0.506849,0.828947,0.7,0.518987,0.68,0.625,0.692308,0.421053,0.472973,0.670886,0.802469,0.688312,0.64,0.582278,0.78481,0.689189] unweighted_recall 0.6305282010573154 [0.886076,0.493506,0.594595,0.5875,0.467532,0.589744,0.584416,0.438356,0.894737,0.653333,0.567568,0.828947,0.6375,0.525641,0.6,0.65,0.717949,0.421053,0.426667,0.675,0.728395,0.657895,0.813333,0.670886,0.666667,0.616438] unweighted_recall 0.6519653839852645 [0.835443,0.513158,0.675676,0.575,0.532468,0.653846,0.576923,0.479452,0.84,0.76,0.554054,0.802632,0.632911,0.512821,0.723684,0.6375,0.848101,0.421053,0.373333,0.65,0.679012,0.802632,0.786667,0.746835,0.666667,0.671233] unweighted_recall 0.6157887849801718 [0.810127,0.381579,0.589041,0.5,0.532468,0.666667,0.641026,0.472973,0.88,0.733333,0.472973,0.815789,0.658228,0.538462,0.513158,0.55,0.759494,0.421053,0.48,0.75,0.580247,0.644737,0.733333,0.64557,0.692308,0.547945] unweighted_recall 0.6280153218801439 [0.860759,0.592105,0.767123,0.575,0.272727,0.597403,0.525641,0.459459,0.933333,0.733333,0.486486,0.776316,0.721519,0.551282,0.657895,0.506173,0.708861,0.513158,0.48,0.675,0.62963,0.723684,0.613333,0.632911,0.705128,0.630137] unweighted_recall 0.6231926124881403 [0.797468,0.513158,0.684932,0.493827,0.480519,0.467532,0.597403,0.364865,0.906667,0.746667,0.567568,0.74026,0.746835,0.525641,0.506667,0.580247,0.74359,0.493333,0.453333,0.7125,0.707317,0.644737,0.75,0.641026,0.734177,0.60274] unweighted_recall 0.6387962117982942 [0.822785,0.532468,0.726027,0.617284,0.571429,0.662338,0.519481,0.391892,0.84,0.8,0.608108,0.815789,0.670886,0.525641,0.733333,0.555556,0.769231,0.4,0.493333,0.6875,0.47561,0.75,0.671053,0.602564,0.708861,0.657534] usercpu_time_millis 195.45800000000213 usercpu_time_millis 178.1530000000089 usercpu_time_millis 184.28300000000775 usercpu_time_millis 178.99700000000962 usercpu_time_millis 176.01600000001838 usercpu_time_millis 174.44499999999152 usercpu_time_millis 183.65099999999757 usercpu_time_millis 183.29800000000773 usercpu_time_millis 176.90200000001255 usercpu_time_millis 176.80000000000007 usercpu_time_millis_testing 10.182000000000357 usercpu_time_millis_testing 8.814000000000988 usercpu_time_millis_testing 9.56899999999905 usercpu_time_millis_testing 8.522000000013463 usercpu_time_millis_testing 8.997000000007915 usercpu_time_millis_testing 9.063999999995076 usercpu_time_millis_testing 9.861999999998261 usercpu_time_millis_testing 9.210000000010155 usercpu_time_millis_testing 9.632000000010521 usercpu_time_millis_testing 8.47899999999413 usercpu_time_millis_training 185.27600000000177 usercpu_time_millis_training 169.3390000000079 usercpu_time_millis_training 174.7140000000087 usercpu_time_millis_training 170.47499999999616 usercpu_time_millis_training 167.01900000001046 usercpu_time_millis_training 165.38099999999645 usercpu_time_millis_training 173.7889999999993 usercpu_time_millis_training 174.08799999999758 usercpu_time_millis_training 167.27000000000203 usercpu_time_millis_training 168.32100000000594 wall_clock_time_millis 198.73404502868652 wall_clock_time_millis 178.74813079833984 wall_clock_time_millis 186.41376495361328 wall_clock_time_millis 180.32312393188477 wall_clock_time_millis 176.4380931854248 wall_clock_time_millis 174.79801177978516 wall_clock_time_millis 185.8956813812256 wall_clock_time_millis 186.4030361175537 wall_clock_time_millis 177.34932899475098 wall_clock_time_millis 177.25682258605957 wall_clock_time_millis_testing 10.237932205200195 wall_clock_time_millis_testing 8.875131607055664 wall_clock_time_millis_testing 9.701967239379883 wall_clock_time_millis_testing 8.535146713256836 wall_clock_time_millis_testing 9.05919075012207 wall_clock_time_millis_testing 9.109973907470703 wall_clock_time_millis_testing 9.987831115722656 wall_clock_time_millis_testing 9.244918823242188 wall_clock_time_millis_testing 9.65118408203125 wall_clock_time_millis_testing 8.484840393066406 wall_clock_time_millis_training 188.49611282348633 wall_clock_time_millis_training 169.87299919128418 wall_clock_time_millis_training 176.7117977142334 wall_clock_time_millis_training 171.78797721862793 wall_clock_time_millis_training 167.37890243530273 wall_clock_time_millis_training 165.68803787231445 wall_clock_time_millis_training 175.90785026550293 wall_clock_time_millis_training 177.15811729431152 wall_clock_time_millis_training 167.69814491271973 wall_clock_time_millis_training 168.77198219299316 weighted_recall 0.6365 [0.759494,0.519481,0.689189,0.530864,0.376623,0.675325,0.558442,0.534247,0.75,0.72973,0.608108,0.855263,0.746835,0.512821,0.546667,0.6375,0.705128,0.513158,0.546667,0.658228,0.695122,0.701299,0.733333,0.74359,0.708861,0.5] weighted_recall 0.6205 [0.833333,0.532468,0.743243,0.518519,0.441558,0.623377,0.649351,0.39726,0.828947,0.716216,0.567568,0.736842,0.632911,0.594937,0.586667,0.5375,0.769231,0.407895,0.44,0.696203,0.740741,0.675325,0.68,0.544304,0.670886,0.554054] weighted_recall 0.641 [0.835443,0.519481,0.716216,0.506173,0.381579,0.602564,0.571429,0.520548,0.894737,0.77027,0.702703,0.789474,0.582278,0.481013,0.626667,0.6875,0.717949,0.381579,0.486486,0.734177,0.703704,0.779221,0.746667,0.670886,0.683544,0.567568] weighted_recall 0.651 [0.860759,0.493506,0.648649,0.5625,0.565789,0.75641,0.675325,0.383562,0.828947,0.813333,0.506849,0.828947,0.7,0.518987,0.68,0.625,0.692308,0.421053,0.472973,0.670886,0.802469,0.688312,0.64,0.582278,0.78481,0.689189] weighted_recall 0.6315 [0.886076,0.493506,0.594595,0.5875,0.467532,0.589744,0.584416,0.438356,0.894737,0.653333,0.567568,0.828947,0.6375,0.525641,0.6,0.65,0.717949,0.421053,0.426667,0.675,0.728395,0.657895,0.813333,0.670886,0.666667,0.616438] weighted_recall 0.6525 [0.835443,0.513158,0.675676,0.575,0.532468,0.653846,0.576923,0.479452,0.84,0.76,0.554054,0.802632,0.632911,0.512821,0.723684,0.6375,0.848101,0.421053,0.373333,0.65,0.679012,0.802632,0.786667,0.746835,0.666667,0.671233] weighted_recall 0.6165 [0.810127,0.381579,0.589041,0.5,0.532468,0.666667,0.641026,0.472973,0.88,0.733333,0.472973,0.815789,0.658228,0.538462,0.513158,0.55,0.759494,0.421053,0.48,0.75,0.580247,0.644737,0.733333,0.64557,0.692308,0.547945] weighted_recall 0.628 [0.860759,0.592105,0.767123,0.575,0.272727,0.597403,0.525641,0.459459,0.933333,0.733333,0.486486,0.776316,0.721519,0.551282,0.657895,0.506173,0.708861,0.513158,0.48,0.675,0.62963,0.723684,0.613333,0.632911,0.705128,0.630137] weighted_recall 0.624 [0.797468,0.513158,0.684932,0.493827,0.480519,0.467532,0.597403,0.364865,0.906667,0.746667,0.567568,0.74026,0.746835,0.525641,0.506667,0.580247,0.74359,0.493333,0.453333,0.7125,0.707317,0.644737,0.75,0.641026,0.734177,0.60274] weighted_recall 0.6385 [0.822785,0.532468,0.726027,0.617284,0.571429,0.662338,0.519481,0.391892,0.84,0.8,0.608108,0.815789,0.670886,0.525641,0.733333,0.555556,0.769231,0.4,0.493333,0.6875,0.47561,0.75,0.671053,0.602564,0.708861,0.657534]