593627 2 Joaquin Vanschoren 14 Supervised Classification 4019 weka.FilteredClassifier_MultiSearch_J48(2) 6405 weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.MultiFilter -F \"weka.filters.unsupervised.attribute.ReplaceMissingNumericValuesAndIndicate \" -F \"weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant -A first-last -N ? -R 0 -F yyyy-MM-dd\\\'T\\\'HH:mm:ss\" -F \"weka.filters.unsupervised.attribute.RemoveUseless -M 99.0\"" -W weka.classifiers.meta.MultiSearch -- -E ACC -search "weka.core.setupgenerator.MathParameter -property confidenceFactor -min -4.0 -max -1.0 -step 1.0 -base 10.0 -expression pow(BASE,I)" -search "weka.core.setupgenerator.MathParameter -property minNumObj -min 0.0 -max 6.0 -step 1.0 -base 2.0 -expression pow(BASE,I)" -class-label 1 -algorithm "weka.classifiers.meta.multisearch.RandomSearch -sample-size 100.0 -num-folds 2 -test-set . -num-iterations 200 -num-slots 1 -S 1 -num-slots 1" -log-file /home/rijnjnvan/apps/weka-3-7-13 -S 1 -W weka.classifiers.trees.J48 -- -C 0.25 -M 2 C 0.25 1720 M 2 1720 F weka.filters.MultiFilter -F "weka.filters.unsupervised.attribute.ReplaceMissingNumericValuesAndIndicate " -F "weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant -A first-last -N ? -R 0 -F yyyy-MM-dd\'T\'HH:mm:ss" -F "weka.filters.unsupervised.attribute.RemoveUseless -M 99.0" 4019 W weka.classifiers.meta.MultiSearch 4019 E ACC 4020 class-label 1 4020 search [weka.core.setupgenerator.MathParameter -property confidenceFactor -min -4.0 -max -1.0 -step 1.0 -base 10.0 -expression pow(BASE,I), weka.core.setupgenerator.MathParameter -property minNumObj -min 0.0 -max 6.0 -step 1.0 -base 2.0 -expression pow(BASE,I)] 4020 algorithm weka.classifiers.meta.multisearch.RandomSearch -sample-size 100.0 -num-folds 2 -test-set . -num-iterations 200 -num-slots 1 -S 1 -num-slots 1 4020 log-file /home/rijnjnvan/apps/weka-3-7-13 4020 S 1 4020 W weka.classifiers.trees.J48 4020 weka weka_3.7.13 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 2057311 description https://api.openml.org/data/download/2057311/weka_generated_run1800369852377716451.xml -1 2057315 model_readable https://api.openml.org/data/download/2057315/WekaModel_weka.classifiers.meta.FilteredClassifier5614405170731027368.model -1 2057313 model_serialized https://api.openml.org/data/download/2057313/WekaSerialized_weka.classifiers.meta.FilteredClassifier7985753835533330281.model -1 2057312 predictions https://api.openml.org/data/download/2057312/weka_generated_predictions7808303024432513454.arff -1 2057314 trace https://api.openml.org/data/download/2057314/optimization_trace1797288030294799779.arff area_under_roc_curve 0.920341 [0.988283,0.894879,0.965608,0.910701,0.864665,0.936871,0.8383,0.951289,0.971788,0.881022] average_cost 0 f_measure 0.775369 [0.977444,0.720988,0.916456,0.794045,0.700252,0.827763,0.444444,0.84689,0.932331,0.593074] kappa 0.753333 kb_relative_information_score 1546.52134 mean_absolute_error 0.051472 mean_prior_absolute_error 0.18 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] os_information [Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64] precision 0.77918 [0.979899,0.712195,0.928205,0.788177,0.705584,0.851852,0.556391,0.811927,0.934673,0.522901] predictive_accuracy 0.778 prior_entropy 3.321928 recall 0.778 [0.975,0.73,0.905,0.8,0.695,0.805,0.37,0.885,0.93,0.685] relative_absolute_error 0.285956 root_mean_prior_squared_error 0.3 root_mean_squared_error 0.19096 root_relative_squared_error 0.636533 scimark_benchmark 896.028697 [550.0601191742942, 1005.4552756626294, 475.31730592400976, 898.676705619265, 1550.6340766572803] total_cost 0 usercpu_time_millis 490 usercpu_time_millis_testing 30 usercpu_time_millis_training 460 area_under_roc_curve 0.954097 [1,0.932083,0.990972,0.890972,0.937361,0.968194,0.899444,0.962083,0.997222,0.962639] area_under_roc_curve 0.913333 [0.972639,0.876528,0.954722,0.917917,0.923056,0.986111,0.74875,0.93,0.936806,0.886806] area_under_roc_curve 0.922903 [0.975,0.835556,0.934028,0.864861,0.885556,0.982639,0.905556,0.919444,1,0.926389] area_under_roc_curve 0.918 [0.997083,0.8875,0.998194,0.981806,0.884583,0.882778,0.862778,0.908472,0.974861,0.801944] area_under_roc_curve 0.918444 [0.997222,0.836944,0.91,0.955139,0.834028,0.929028,0.864444,0.950278,0.997083,0.910278] area_under_roc_curve 0.945931 [1,0.983056,0.999722,0.893333,0.877222,0.961111,0.860417,0.973056,0.994722,0.916667] area_under_roc_curve 0.886611 [0.975,0.905,0.922222,0.888333,0.755556,0.855556,0.849167,0.912778,0.972222,0.830278] area_under_roc_curve 0.927972 [0.971667,0.889306,0.997083,0.899167,0.846111,0.959861,0.898889,0.988889,0.93375,0.895] area_under_roc_curve 0.926736 [1,0.921111,0.994444,0.940556,0.89875,0.918333,0.791944,0.990278,1,0.811944] area_under_roc_curve 0.891583 [1,0.85875,0.963889,0.865556,0.858333,0.949722,0.682083,0.963333,0.910278,0.863889] 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 0.76971 [1,0.717949,0.9,0.780488,0.666667,0.894737,0.230769,0.871795,0.9,0.734694] f_measure 0.755139 [0.974359,0.619048,0.894737,0.769231,0.769231,0.837209,0.457143,0.761905,0.923077,0.545455] f_measure 0.76763 [0.974359,0.682927,0.864865,0.684211,0.780488,0.878049,0.47619,0.871795,0.97561,0.487805] f_measure 0.771668 [0.95,0.714286,0.95,0.826087,0.731707,0.756757,0.590909,0.810811,0.974359,0.411765] f_measure 0.759257 [0.952381,0.514286,0.918919,0.809524,0.685714,0.756757,0.611111,0.782609,0.909091,0.652174] f_measure 0.7829 [1,0.878049,0.952381,0.75,0.6,0.833333,0.424242,0.869565,0.95,0.571429] f_measure 0.747666 [0.974359,0.8,0.894737,0.8,0.578947,0.714286,0.363636,0.829268,0.95,0.571429] f_measure 0.773475 [0.95,0.75,0.95,0.761905,0.6,0.842105,0.444444,0.904762,0.864865,0.666667] f_measure 0.815935 [1,0.780488,0.95,0.923077,0.820513,0.820513,0.4,0.904762,1,0.56] f_measure 0.784271 [1,0.727273,0.883721,0.833333,0.777778,0.947368,0.296296,0.863636,0.871795,0.641509] kappa 0.761111 kappa 0.727778 kappa 0.738889 kappa 0.75 kappa 0.738889 kappa 0.766667 kappa 0.722222 kappa 0.755556 kappa 0.8 kappa 0.772222 kb_relative_information_score 155.359726 kb_relative_information_score 148.398634 kb_relative_information_score 151.639734 kb_relative_information_score 156.159855 kb_relative_information_score 151.036384 kb_relative_information_score 156.332477 kb_relative_information_score 151.746507 kb_relative_information_score 155.392744 kb_relative_information_score 163.171728 kb_relative_information_score 157.28355 mean_absolute_error 0.05408 mean_absolute_error 0.055895 mean_absolute_error 0.057819 mean_absolute_error 0.049087 mean_absolute_error 0.053659 mean_absolute_error 0.052929 mean_absolute_error 0.050552 mean_absolute_error 0.053659 mean_absolute_error 0.042566 mean_absolute_error 0.044472 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 mean_prior_absolute_error 0.18 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.783005 [1,0.736842,0.9,0.761905,0.571429,0.944444,0.5,0.894737,0.9,0.62069] precision 0.760488 [1,0.590909,0.944444,0.789474,0.789474,0.782609,0.533333,0.727273,0.947368,0.5] precision 0.772697 [1,0.666667,0.941176,0.722222,0.761905,0.857143,0.454545,0.894737,0.952381,0.47619] precision 0.777442 [0.95,0.681818,0.95,0.730769,0.714286,0.823529,0.541667,0.882353,1,0.5] precision 0.769541 [0.909091,0.6,1,0.772727,0.8,0.823529,0.6875,0.692308,0.833333,0.576923] precision 0.785688 [1,0.857143,0.909091,0.75,0.6,0.9375,0.538462,0.769231,0.95,0.545455] precision 0.754119 [1,0.8,0.944444,0.8,0.611111,0.681818,0.461538,0.809524,0.95,0.482759] precision 0.805753 [0.95,0.75,0.95,0.727273,0.6,0.888889,0.857143,0.863636,0.941176,0.529412] precision 0.827379 [1,0.761905,0.95,0.947368,0.842105,0.842105,0.6,0.863636,1,0.466667] precision 0.807824 [1,0.666667,0.826087,0.9375,0.875,1,0.571429,0.791667,0.894737,0.515152] predictive_accuracy 0.785 predictive_accuracy 0.755 predictive_accuracy 0.765 predictive_accuracy 0.775 predictive_accuracy 0.765 predictive_accuracy 0.79 predictive_accuracy 0.75 predictive_accuracy 0.78 predictive_accuracy 0.82 predictive_accuracy 0.795 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 prior_entropy 3.321928 recall 0.785 [1,0.7,0.9,0.8,0.8,0.85,0.15,0.85,0.9,0.9] recall 0.755 [0.95,0.65,0.85,0.75,0.75,0.9,0.4,0.8,0.9,0.6] recall 0.765 [0.95,0.7,0.8,0.65,0.8,0.9,0.5,0.85,1,0.5] recall 0.775 [0.95,0.75,0.95,0.95,0.75,0.7,0.65,0.75,0.95,0.35] recall 0.765 [1,0.45,0.85,0.85,0.6,0.7,0.55,0.9,1,0.75] recall 0.79 [1,0.9,1,0.75,0.6,0.75,0.35,1,0.95,0.6] recall 0.75 [0.95,0.8,0.85,0.8,0.55,0.75,0.3,0.85,0.95,0.7] recall 0.78 [0.95,0.75,0.95,0.8,0.6,0.8,0.3,0.95,0.8,0.9] recall 0.82 [1,0.8,0.95,0.9,0.8,0.8,0.3,0.95,1,0.7] recall 0.795 [1,0.8,0.95,0.75,0.7,0.9,0.2,0.95,0.85,0.85] relative_absolute_error 0.300447 relative_absolute_error 0.31053 relative_absolute_error 0.321215 relative_absolute_error 0.272708 relative_absolute_error 0.298108 relative_absolute_error 0.294051 relative_absolute_error 0.280844 relative_absolute_error 0.298107 relative_absolute_error 0.236478 relative_absolute_error 0.247068 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_prior_squared_error 0.3 root_mean_squared_error 0.178281 root_mean_squared_error 0.204674 root_mean_squared_error 0.189736 root_mean_squared_error 0.193873 root_mean_squared_error 0.195618 root_mean_squared_error 0.178004 root_mean_squared_error 0.211307 root_mean_squared_error 0.1858 root_mean_squared_error 0.173815 root_mean_squared_error 0.195086 root_relative_squared_error 0.594271 root_relative_squared_error 0.682247 root_relative_squared_error 0.632454 root_relative_squared_error 0.646244 root_relative_squared_error 0.65206 root_relative_squared_error 0.593348 root_relative_squared_error 0.704356 root_relative_squared_error 0.619332 root_relative_squared_error 0.579385 root_relative_squared_error 0.650288 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 930 usercpu_time_millis 810 usercpu_time_millis 460 usercpu_time_millis 550 usercpu_time_millis 590 usercpu_time_millis 590 usercpu_time_millis 610 usercpu_time_millis 580 usercpu_time_millis 620 usercpu_time_millis 630 usercpu_time_millis_testing 20 usercpu_time_millis_testing 10 usercpu_time_millis_testing 10 usercpu_time_millis_testing 10 usercpu_time_millis_testing 10 usercpu_time_millis_testing 10 usercpu_time_millis_testing 10 usercpu_time_millis_testing 10 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_training 910 usercpu_time_millis_training 800 usercpu_time_millis_training 450 usercpu_time_millis_training 540 usercpu_time_millis_training 580 usercpu_time_millis_training 580 usercpu_time_millis_training 600 usercpu_time_millis_training 570 usercpu_time_millis_training 620 usercpu_time_millis_training 630