2040441 2742 Wouter Nuijten 145682 Supervised Classification area_under_roc_curve 6138 weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_RandomForest(1) 181164 weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.unsupervised.attribute.InterquartileRange -R first-last -O 3.0 -E 6.0" -W weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.unsupervised.instance.RemoveWithValues -S 0.0 -C 103 -L 2" -W weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.unsupervised.attribute.PrincipalComponents -R 0.95 -A 5 -M 16" -W weka.classifiers.trees.RandomForest -- -P 100 -I 1000 -num-slots 1 -K 0 -M 1.0 -V 0.001 -S 1 P 100 5923 I 1000 5923 num-slots 1 5923 K 0 5923 M 1.0 5923 V 0.001 5923 S 1 5923 F weka.filters.unsupervised.attribute.PrincipalComponents -R 0.95 -A 5 -M 16 6105 W weka.classifiers.trees.RandomForest 6105 F weka.filters.unsupervised.instance.RemoveWithValues -S 0.0 -C 103 -L 2 6124 W weka.classifiers.meta.FilteredClassifier 6124 F weka.filters.unsupervised.attribute.InterquartileRange -R first-last -O 3.0 -E 6.0 6138 W weka.classifiers.meta.FilteredClassifier 6138 weka weka_3.8.1 313 spectrometer https://www.openml.org/data/download/52217/phpHNcI2h -1 5030723 description https://api.openml.org/data/download/5030723/weka_generated_run1311763837423111172.xml -1 5030725 model_readable https://api.openml.org/data/download/5030725/WekaModel_weka.classifiers.meta.FilteredClassifier8120594205037962183.model -1 5030724 model_serialized https://api.openml.org/data/download/5030724/WekaSerialized_weka.classifiers.meta.FilteredClassifier2477571906180797239.model -1 5030726 predictions https://api.openml.org/data/download/5030726/weka_generated_predictions7595643672470181242.arff area_under_roc_curve 0.929481 [0.761364,0.357547,0.704198,0.437736,0.797732,0.94476,0.978503,0.987385,0.980175,0.986031,0.996649,0.851034,0.918614,0.927065,0.955027,0.913292,0.934098,0.913479,0.914135,0.97987,0.951149,0.969674,0.958966,0.995731,0.941604,0.430189,0.39717,0.995581,0.996843,0.852892,0.95471,0.928131,0.980886,0.989734,0.431132,0.971172,0.39434,0.395283,0.430189,0.987058,0.982323,0.88327,0.454717,0.424528,0.997475,0.400943,0.446226,0.415094] average_cost 0 f_measure 0.434971 [0,0,0,0,0,0,0.352941,0.727273,0.608696,0.592593,0.792453,0.333333,0.474576,0.346667,0.363636,0.153846,0.507463,0.266667,0.438095,0.680412,0.315789,0.5,0,0.333333,0,0,0,0.75,0.4,0,0.594595,0.25641,0.4375,0,0,0,0,0,0,0,0.4,0,0,0,0.666667,0,0,0] kappa 0.426853 kb_relative_information_score 255.959077 mean_absolute_error 0.029559 mean_prior_absolute_error 0.039641 number_of_instances 531 [3,1,7,1,2,3,10,24,13,12,26,15,27,31,19,19,30,35,42,55,9,10,4,4,3,1,1,3,3,8,45,20,18,5,1,2,1,1,1,3,3,2,1,1,3,1,1,1] precision 0.432828 [0,0,0,0,0,0,0.428571,0.645161,0.7,0.533333,0.777778,0.285714,0.4375,0.295455,0.428571,0.285714,0.459459,0.25,0.365079,0.785714,0.3,0.666667,0,0.5,0,0,0,0.6,0.5,0,0.5,0.263158,0.5,0,0,0,0,0,0,0,0.5,0,0,0,0.5,0,0,0] predictive_accuracy 0.45951 prior_entropy 4.846691 recall 0.45951 [0,0,0,0,0,0,0.3,0.833333,0.538462,0.666667,0.807692,0.4,0.518519,0.419355,0.315789,0.105263,0.566667,0.285714,0.547619,0.6,0.333333,0.4,0,0.25,0,0,0,1,0.333333,0,0.733333,0.25,0.388889,0,0,0,0,0,0,0,0.333333,0,0,0,1,0,0,0] relative_absolute_error 0.74565 root_mean_prior_squared_error 0.140616 root_mean_squared_error 0.118121 root_relative_squared_error 0.84003 total_cost 0 area_under_roc_curve 0.93415 [0.0,0.0,1,0.0,0.0,1,0.981132,1,0.981132,0.981132,1,0.961538,0.96732,0.934641,0.961538,0.971154,0.928105,0.94,0.93,0.979592,0.943396,1,0.0,1,0.0,0.0,0.0,0.0,0.0,0.632075,0.963265,1,0.985577,0.0,0.5,0.0,0.0,0.0,0.5,0.981132,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5] area_under_roc_curve 0.915711 [0.0,0.0,0.586538,0.5,0.865385,0.961538,1,1,0.980769,0.980769,0.993333,0.921569,0.973333,0.946667,0.960784,0.823529,0.9,0.94898,0.918367,0.970833,0.884615,1,0.0,0.980769,0.0,0.5,0.0,0.0,0.0,0.923077,0.923469,0.75,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] area_under_roc_curve 0.925958 [0.0,0.0,0.230769,0.0,0.884615,0.0,0.980769,1,1,0.980769,0.986667,0.485294,0.75,0.993333,1,0.897059,0.933333,0.98,0.959184,0.968085,0.923077,0.980769,0.0,1,0.0,0.0,0.0,1,0.0,0.971154,0.994898,0.95098,0.960784,0.980769,0.0,0.0,0.0,0.0,0.0,0.0,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0] area_under_roc_curve 0.967801 [0.0,0.0,1,0.0,0.0,0.0,1,1,1,0.980769,0.993333,0.960784,0.966667,0.94,0.941176,0.882353,0.966667,0.926667,0.918367,0.994681,1,0.942308,0.961538,1,0.0,0.0,0.0,1,0.0,1,0.964286,1,0.980769,1,0.0,0.0,0.0,0.0,0.0,0.0,0.980769,0.0,0.0,0.0,0.0,0.0,0.0,0.0] area_under_roc_curve 0.9311 [0.0,0.5,0.451923,0.0,0.0,0.0,0.980769,0.993333,0.990196,1,1,0.573529,1,0.986667,0.911765,0.903846,0.926667,0.92,0.938776,0.992908,1,0.923077,0.980769,0.0,0.0,0.0,0.0,1,0.0,0.846154,0.938776,0.941176,0.980769,1,0.0,0.0,0.0,0.0,0.0,0.0,1,0.0,0.0,0.0,1,0.0,0.0,0.0] area_under_roc_curve 0.951649 [0.0,0.0,0.980769,0.0,0.0,0.0,0.961538,0.973333,0.980392,0.942308,1,0.961538,0.882353,0.94,0.960784,0.980392,0.96,0.866667,0.933673,0.992908,0.951923,1,0.980769,0.0,0.0,0.0,0.0,0.0,1,0.817308,0.918367,0.872549,0.970588,0.961538,0.0,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1,0.0,0.0,0.0] area_under_roc_curve 0.959205 [0.0,0.0,1,0.0,0.0,0.0,1,0.993333,0.916667,1,1,1,0.95098,0.953333,1,0.941176,0.953333,0.886667,0.872449,0.980496,0.0,0.942308,1,0.0,0.0,0.0,0.0,0.0,1,0.0,0.979167,0.901961,0.980392,0.980769,0.0,0.961538,0.0,0.0,0.0,0.0,0.0,0.942308,0.0,0.0,1,0.0,0.0,0.0] area_under_roc_curve 0.916554 [0.923077,0.0,0.0,0.0,0.0,0.0,0.932692,0.990196,1,1,1,1,0.893333,0.918367,0.941176,0.921569,0.886667,0.806122,0.860417,0.995833,1,0.942308,0.0,0.0,0.961538,0.0,0.0,0.0,1,0.0,0.945833,0.980392,0.970588,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.961538,0.5,0.0,0.0,0.0,0.5,0.0] area_under_roc_curve 0.920636 [0.817308,0.0,0.0,0.0,0.0,0.0,1,0.970588,1,1,1,0.961538,0.94,0.776667,1,0.892157,0.926667,0.961735,0.941667,0.958333,0.980769,1,0.0,0.0,1,0.0,0.0,0.0,0.0,0.884615,0.933333,0.990196,1,0.0,0.0,0.0,0.5,0.0,0.0,1,0.0,0.0,0.0,0.5,0.0,0.5,0.0,0.0] area_under_roc_curve 0.940985 [0.798077,0.0,0.0,0.0,0.0,0.980769,0.942308,0.955882,1,1,1,0.942308,0.953333,0.913333,1,0.960784,0.933333,0.969388,0.928571,0.970833,0.980769,0.980769,0.0,0.0,0.961538,0.0,0.5,0.0,0.0,0.826923,0.983333,0.941176,0.990196,0.0,0.0,0.0,0.0,0.5,0.0,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] 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 average_cost 0 f_measure 0.278643 [0,0,0,0,0,0,0.666667,0.666667,0,0,0.666667,0,0.4,0.25,0,0,0.444444,0.25,0.4,0.444444,0,0.666667,0,0,0,0,0,0,0,0,0.588235,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] f_measure 0.331207 [0,0,0,0,0,0,0,0.571429,0,0.5,0.5,0.4,0.5,0.4,0,0,0.4,0,0.4,0.666667,0,1,0,0,0,0,0,0,0,0,0.444444,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] f_measure 0.478192 [0,0,0,0,0,0,0,0.8,0.666667,0,0.857143,0,0.5,0.545455,0.666667,0,0.333333,0.545455,0.5,0.6,0,0,0,1,0,0,0,1,0,0,1,0.5,0.4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] f_measure 0.466038 [0,0,0,0,0,0,0,1,1,0,0.666667,0.5,0.4,0.444444,0,0,0.666667,0.4,0.5,0.8,0.5,0,0,0,0,0,0,1,0,0,0.666667,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] f_measure 0.517063 [0,0,0,0,0,0,0,0.857143,0.5,1,1,0,0.571429,0.5,0.5,0,0.571429,0,0.6,0.909091,0.5,0,0,0,0,0,0,1,0,0,0.363636,0.5,0.666667,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0] f_measure 0.375502 [0,0,0,0,0,0,0,0.571429,0,0,0.857143,0,0.333333,0.285714,0,0,0.571429,0,0.5,0.8,0,1,0,0,0,0,0,0,1,0,0.444444,0,0.4,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0] f_measure 0.461766 [0,0,0,0,0,0,1,0.857143,0.666667,0.666667,0.8,1,0.571429,0.285714,0,0.666667,0.571429,0,0.363636,0.666667,0,0,0,0,0,0,0,0,0,0,0.6,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0] f_measure 0.350739 [0,0,0,0,0,0,0,0.666667,1,0.666667,0.8,0.666667,0.5,0.285714,0.5,0,0.285714,0.181818,0.285714,0.8,0,0,0,0,0,0,0,0,0,0,0.533333,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] f_measure 0.437788 [0,0,0,0,0,0,0.666667,0.666667,1,1,0.666667,0.666667,0.285714,0,0.666667,0,0.571429,0.545455,0.444444,0.5,0,1,0,0,0,0,0,0,0,0,0.545455,0.5,0.666667,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] f_measure 0.472727 [0,0,0,0,0,0,0,0.5,1,0.8,1,0.333333,0.666667,0.4,1,0.5,0.666667,0.25,0.363636,0.5,1,0,0,0,0,0,0,0,0,0,0.833333,0.4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] kappa 0.309463 kappa 0.340746 kappa 0.500377 kappa 0.460407 kappa 0.540693 kappa 0.379766 kappa 0.45857 kappa 0.357089 kappa 0.440422 kappa 0.480784 kb_relative_information_score 25.216264 kb_relative_information_score 21.992777 kb_relative_information_score 26.757101 kb_relative_information_score 28.757219 kb_relative_information_score 26.278952 kb_relative_information_score 27.064048 kb_relative_information_score 27.488169 kb_relative_information_score 22.023627 kb_relative_information_score 24.279986 kb_relative_information_score 26.100934 mean_absolute_error 0.030301 mean_absolute_error 0.03087 mean_absolute_error 0.028533 mean_absolute_error 0.02864 mean_absolute_error 0.029208 mean_absolute_error 0.029671 mean_absolute_error 0.028289 mean_absolute_error 0.030904 mean_absolute_error 0.029803 mean_absolute_error 0.029351 mean_prior_absolute_error 0.039681 mean_prior_absolute_error 0.039673 mean_prior_absolute_error 0.039638 mean_prior_absolute_error 0.039627 mean_prior_absolute_error 0.039672 mean_prior_absolute_error 0.039645 mean_prior_absolute_error 0.039604 mean_prior_absolute_error 0.039587 mean_prior_absolute_error 0.039629 mean_prior_absolute_error 0.039657 number_of_instances 54 [0,0,1,0,0,1,1,2,1,1,2,2,3,3,2,2,3,4,4,5,1,1,0,1,0,0,0,0,0,1,5,2,2,0,1,0,0,0,1,1,0,0,0,0,0,0,0,1] number_of_instances 53 [0,0,1,1,1,1,1,2,1,1,3,2,3,3,2,2,3,4,4,5,1,1,0,1,0,1,0,0,0,1,4,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] number_of_instances 53 [0,0,1,0,1,0,1,2,1,1,3,2,3,3,2,2,3,3,4,6,1,1,0,1,0,0,0,1,0,1,4,2,2,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0] number_of_instances 53 [0,0,1,0,0,0,1,3,1,1,3,2,3,3,2,2,3,3,4,6,1,1,1,1,0,0,0,1,0,1,4,2,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0] number_of_instances 53 [0,1,1,0,0,0,1,3,2,1,3,2,2,3,2,1,3,3,4,6,1,1,1,0,0,0,0,1,0,1,4,2,1,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0] number_of_instances 53 [0,0,1,0,0,0,1,3,2,1,3,1,2,3,2,2,3,3,4,6,1,1,1,0,0,0,0,0,1,1,4,2,2,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0] number_of_instances 53 [0,0,1,0,0,0,1,3,2,1,3,1,2,3,2,2,3,3,4,6,0,1,1,0,0,0,0,0,1,0,5,2,2,1,0,1,0,0,0,0,0,1,0,0,1,0,0,0] number_of_instances 53 [1,0,0,0,0,0,1,2,1,1,2,1,3,4,2,2,3,4,5,5,1,1,0,0,1,0,0,0,1,0,5,2,2,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0] number_of_instances 53 [1,0,0,0,0,0,1,2,1,2,2,1,3,3,1,2,3,4,5,5,1,1,0,0,1,0,0,0,0,1,5,2,2,0,0,0,1,0,0,1,0,0,0,1,0,1,0,0] number_of_instances 53 [1,0,0,0,0,1,1,2,1,2,2,1,3,3,2,2,3,4,4,5,1,1,0,0,1,0,1,0,0,1,5,2,2,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0] precision 0.259568 [0,0,0,0,0,0,0.5,0.5,0,0,1,0,0.5,0.2,0,0,0.333333,0.25,0.333333,0.5,0,0.5,0,0,0,0,0,0,0,0,0.416667,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] precision 0.369775 [0,0,0,0,0,0,0,0.4,0,0.333333,1,0.333333,1,0.285714,0,0,0.5,0,0.272727,0.75,0,1,0,0,0,0,0,0,0,0,0.4,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] precision 0.5 [0,0,0,0,0,0,0,0.666667,0.5,0,0.75,0,1,0.375,1,0,0.333333,0.375,0.5,0.75,0,0,0,1,0,0,0,1,0,0,1,0.5,0.333333,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] precision 0.476101 [0,0,0,0,0,0,0,1,1,0,0.666667,0.5,0.5,0.333333,0,0,0.666667,0.5,0.375,1,0.333333,0,0,0,0,0,0,1,0,0,0.6,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] precision 0.519362 [0,0,0,0,0,0,0,0.75,0.5,1,1,0,0.4,1,0.5,0,0.5,0,0.5,1,0.333333,0,0,0,0,0,0,1,0,0,0.285714,0.5,0.5,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0] precision 0.363522 [0,0,0,0,0,0,0,0.5,0,0,0.75,0,0.25,0.25,0,0,0.5,0,0.375,1,0,1,0,0,0,0,0,0,1,0,0.4,0,0.333333,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0] precision 0.47062 [0,0,0,0,0,0,1,0.75,1,0.5,1,1,0.4,0.25,0,1,0.5,0,0.285714,0.666667,0,0,0,0,0,0,0,0,0,0,0.6,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0] precision 0.352606 [0,0,0,0,0,0,0,1,1,0.5,0.666667,0.5,0.4,0.333333,0.5,0,0.25,0.142857,0.5,0.8,0,0,0,0,0,0,0,0,0,0,0.4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] precision 0.449012 [0,0,0,0,0,0,0.5,1,1,1,0.5,0.5,0.25,0,0.5,0,0.5,0.428571,0.5,0.666667,0,1,0,0,0,0,0,0,0,0,0.5,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] precision 0.466936 [0,0,0,0,0,0,0,0.5,1,0.666667,1,0.2,0.666667,0.5,1,0.5,0.666667,0.25,0.285714,0.666667,1,0,0,0,0,0,0,0,0,0,0.714286,0.333333,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] predictive_accuracy 0.351852 predictive_accuracy 0.377358 predictive_accuracy 0.528302 predictive_accuracy 0.490566 predictive_accuracy 0.566038 predictive_accuracy 0.415094 predictive_accuracy 0.490566 predictive_accuracy 0.396226 predictive_accuracy 0.471698 predictive_accuracy 0.509434 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 prior_entropy 4.846691 recall 0.351852 [0,0,0,0,0,0,1,1,0,0,0.5,0,0.333333,0.333333,0,0,0.666667,0.25,0.5,0.4,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.377358 [0,0,0,0,0,0,0,1,0,1,0.333333,0.5,0.333333,0.666667,0,0,0.333333,0,0.75,0.6,0,1,0,0,0,0,0,0,0,0,0.5,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.528302 [0,0,0,0,0,0,0,1,1,0,1,0,0.333333,1,0.5,0,0.333333,1,0.5,0.5,0,0,0,1,0,0,0,1,0,0,1,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.490566 [0,0,0,0,0,0,0,1,1,0,0.666667,0.5,0.333333,0.666667,0,0,0.666667,0.333333,0.75,0.666667,1,0,0,0,0,0,0,1,0,0,0.75,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.566038 [0,0,0,0,0,0,0,1,0.5,1,1,0,1,0.333333,0.5,0,0.666667,0,0.75,0.833333,1,0,0,0,0,0,0,1,0,0,0.5,0.5,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0] recall 0.415094 [0,0,0,0,0,0,0,0.666667,0,0,1,0,0.5,0.333333,0,0,0.666667,0,0.75,0.666667,0,1,0,0,0,0,0,0,1,0,0.5,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0] recall 0.490566 [0,0,0,0,0,0,1,1,0.5,1,0.666667,1,1,0.333333,0,0.5,0.666667,0,0.5,0.666667,0,0,0,0,0,0,0,0,0,0,0.6,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0] recall 0.396226 [0,0,0,0,0,0,0,0.5,1,1,1,1,0.666667,0.25,0.5,0,0.333333,0.25,0.2,0.8,0,0,0,0,0,0,0,0,0,0,0.8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.471698 [0,0,0,0,0,0,1,0.5,1,1,1,1,0.333333,0,1,0,0.666667,0.75,0.4,0.4,0,1,0,0,0,0,0,0,0,0,0.6,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.509434 [0,0,0,0,0,0,0,0.5,1,1,1,1,0.666667,0.333333,1,0.5,0.666667,0.25,0.5,0.4,1,0,0,0,0,0,0,0,0,0,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 0.763613 relative_absolute_error 0.77811 relative_absolute_error 0.719838 relative_absolute_error 0.722733 relative_absolute_error 0.736244 relative_absolute_error 0.748429 relative_absolute_error 0.714301 relative_absolute_error 0.780672 relative_absolute_error 0.752069 relative_absolute_error 0.74013 root_mean_prior_squared_error 0.140756 root_mean_prior_squared_error 0.140729 root_mean_prior_squared_error 0.140604 root_mean_prior_squared_error 0.140565 root_mean_prior_squared_error 0.140725 root_mean_prior_squared_error 0.140628 root_mean_prior_squared_error 0.140483 root_mean_prior_squared_error 0.14042 root_mean_prior_squared_error 0.14057 root_mean_prior_squared_error 0.140671 root_mean_squared_error 0.120259 root_mean_squared_error 0.122621 root_mean_squared_error 0.116229 root_mean_squared_error 0.113844 root_mean_squared_error 0.116879 root_mean_squared_error 0.119218 root_mean_squared_error 0.114686 root_mean_squared_error 0.121974 root_mean_squared_error 0.117595 root_mean_squared_error 0.117542 root_relative_squared_error 0.854378 root_relative_squared_error 0.871322 root_relative_squared_error 0.826644 root_relative_squared_error 0.809905 root_relative_squared_error 0.83055 root_relative_squared_error 0.847755 root_relative_squared_error 0.816367 root_relative_squared_error 0.868637 root_relative_squared_error 0.83656 root_relative_squared_error 0.835575 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