Task
Supervised Classification on anneal

Supervised Classification on anneal

Task 2 Supervised Classification anneal 5745 runs submitted
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  • at2 basic d3m study_1 study_107 study_14 study_41 study_70 study_73 under100k
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5745 results
Tan Zheng 4 years ago
ran flow weka.classifiers.trees.RandomTree(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9415, f_measure: 0.9251, kappa: 0.8138, kb_relative_information_score: 0.7651, mean_absolute_error: 0.0385, mean_prior_absolute_error: 0.1343, weighted_recall: 0.9254, number_of_instances: 898, precision: 0.9262, predictive_accuracy: 0.9254, prior_entropy: 1.1915, relative_absolute_error: 0.2867, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1472, root_relative_squared_error: 0.5702, scimark_benchmark: 2015.8127,
Tan Zheng 4 years ago
ran flow weka.classifiers.functions.SGD(2) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Client side error: weka.classifiers.functions.SGD: Cannot handle multi-valued nominal class! Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
Tan Zheng 4 years ago
ran flow weka.classifiers.trees.DecisionStump(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8519, kappa: 0.4503, kb_relative_information_score: 0.3585, mean_absolute_error: 0.0952, mean_prior_absolute_error: 0.1343, weighted_recall: 0.7717, number_of_instances: 898, predictive_accuracy: 0.7717, prior_entropy: 1.1915, relative_absolute_error: 0.7089, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2183, root_relative_squared_error: 0.8453, scimark_benchmark: 2015.8127,
Tan Zheng 4 years ago
ran flow weka.classifiers.trees.LMT(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.979, f_measure: 0.9555, kappa: 0.8893, kb_relative_information_score: 0.8725, mean_absolute_error: 0.0191, mean_prior_absolute_error: 0.1343, weighted_recall: 0.9555, number_of_instances: 898, precision: 0.9556, predictive_accuracy: 0.9555, prior_entropy: 1.1915, relative_absolute_error: 0.1424, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1163, root_relative_squared_error: 0.4505, scimark_benchmark: 2127.2943,
Tan Zheng 4 years ago
ran flow weka.classifiers.trees.J48(3) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9679, f_measure: 0.9096, kappa: 0.772, kb_relative_information_score: 0.7382, mean_absolute_error: 0.0437, mean_prior_absolute_error: 0.1343, weighted_recall: 0.912, number_of_instances: 898, precision: 0.9097, predictive_accuracy: 0.912, prior_entropy: 1.1915, relative_absolute_error: 0.3255, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1461, root_relative_squared_error: 0.5659, scimark_benchmark: 2100.1601,
Arlind Kadra 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ses.DecisionTreeClassifier)(3) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9602, f_measure: 0.9277, kappa: 0.8245, kb_relative_information_score: 0.7656, mean_absolute_error: 0.0347, mean_prior_absolute_error: 0.1343, weighted_recall: 0.9321, number_of_instances: 898, precision: 0.924, predictive_accuracy: 0.9321, prior_entropy: 1.1915, relative_absolute_error: 0.2583, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1389, root_relative_squared_error: 0.5378,
Arlind Kadra 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ses.DecisionTreeClassifier)(3) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9573, f_measure: 0.9265, kappa: 0.8212, kb_relative_information_score: 0.7613, mean_absolute_error: 0.0351, mean_prior_absolute_error: 0.1343, weighted_recall: 0.931, number_of_instances: 898, precision: 0.9229, predictive_accuracy: 0.931, prior_entropy: 1.1915, relative_absolute_error: 0.261, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1402, root_relative_squared_error: 0.543,
chimi wangmo 5 years ago
ran flow weka.classifiers.functions.Logistic(3) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9307, f_measure: 0.8667, kappa: 0.6695, kb_relative_information_score: 0.6478, mean_absolute_error: 0.0546, mean_prior_absolute_error: 0.1343, weighted_recall: 0.8708, number_of_instances: 898, precision: 0.8684, predictive_accuracy: 0.8708, prior_entropy: 1.1915, relative_absolute_error: 0.4062, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1805, root_relative_squared_error: 0.699, scimark_benchmark: 1015.7068,
Donghyok Shin 5 years ago
ran flow weka.classifiers.rules.ZeroR(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4915, kb_relative_information_score: -0.0014, mean_absolute_error: 0.1344, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.1915, recall: 0.7617, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1, scimark_benchmark: 1148.7037,
T I 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ee.DecisionTreeClassifier)(15) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9918, f_measure: 0.9911, kappa: 0.9779, kb_relative_information_score: 855.9874, mean_absolute_error: 0.003, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9912, predictive_accuracy: 0.9911, prior_entropy: 1.2149, recall: 0.9911, relative_absolute_error: 0.0221, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.0545, root_relative_squared_error: 0.211,
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.IBk(14) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.IBk(14) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.IBk(14) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.IBk(14) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Jeroen Gommers 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Armin Ott 7 years ago
ran flow mlr.classif.cforest(5) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6587, kb_relative_information_score: 203.0276, mean_absolute_error: 0.0794, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.5802, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.5915, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2818, root_relative_squared_error: 1.0915, usercpu_time_millis: 27.32, usercpu_time_millis_testing: 3.77, usercpu_time_millis_training: 23.55,
Isabel van den Heuvel 7 years ago
ran flow weka.MultiSearch(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Isabel van den Heuvel 7 years ago
ran flow weka.FilteredClassifier(2) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Isabel van den Heuvel 7 years ago
ran flow weka.FilteredClassifier(2) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Isabel van den Heuvel 7 years ago
ran flow weka.FilteredClassifier(2) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Fenna Blom 7 years ago
ran flow weka.J48(41) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Isabel van den Heuvel 7 years ago
ran flow weka.J48(41) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
Isabel van den Heuvel 7 years ago
ran flow weka.ZeroR(17) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
William Raynaut 7 years ago
ran flow weka.kf.AdaBoostM1-HoeffdingTree(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4918, f_measure: 0.6587, kb_relative_information_score: -63.2957, mean_absolute_error: 0.1432, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.5802, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 1.0664, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2636, root_relative_squared_error: 1.0208,
William Raynaut 7 years ago
ran flow weka.kf.Bagging-JRip(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9865, f_measure: 0.9606, kappa: 0.9014, kb_relative_information_score: 762.7124, mean_absolute_error: 0.0234, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9606, predictive_accuracy: 0.961, prior_entropy: 1.2149, recall: 0.961, relative_absolute_error: 0.1739, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1016, root_relative_squared_error: 0.3936,
William Raynaut 7 years ago
ran flow weka.kf.JRip(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.95, f_measure: 0.9503, kappa: 0.8763, kb_relative_information_score: 740.149, mean_absolute_error: 0.0232, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9499, predictive_accuracy: 0.951, prior_entropy: 1.2149, recall: 0.951, relative_absolute_error: 0.1727, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1173, root_relative_squared_error: 0.4542,
William Raynaut 7 years ago
ran flow weka.kf.Bagging-HoeffdingTree(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5147, f_measure: 0.6587, kb_relative_information_score: 0.4357, mean_absolute_error: 0.1349, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.5802, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 1.0044, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2573, root_relative_squared_error: 0.9964,
William Raynaut 7 years ago
ran flow weka.kf.HoeffdingTree(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4915, f_measure: 0.6587, kb_relative_information_score: -1.2439, mean_absolute_error: 0.1344, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.5802, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1,
William Raynaut 7 years ago
ran flow weka.kf.AdaBoostM1-IBk5(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9583, f_measure: 0.9642, kappa: 0.9103, kb_relative_information_score: 788.2039, mean_absolute_error: 0.013, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9642, predictive_accuracy: 0.9644, prior_entropy: 1.2149, recall: 0.9644, relative_absolute_error: 0.097, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1058, root_relative_squared_error: 0.4097,
William Raynaut 7 years ago
ran flow weka.kf.AdaBoostM1-J48(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9883, f_measure: 0.9499, kappa: 0.875, kb_relative_information_score: 773.8924, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.95, predictive_accuracy: 0.9499, prior_entropy: 1.2149, recall: 0.9499, relative_absolute_error: 0.124, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1229, root_relative_squared_error: 0.4758,
William Raynaut 7 years ago
ran flow weka.kf.AdaBoostM1-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9408, f_measure: 0.8215, kappa: 0.6266, kb_relative_information_score: 200.7674, mean_absolute_error: 0.1259, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8864, predictive_accuracy: 0.8051, prior_entropy: 1.2149, recall: 0.8051, relative_absolute_error: 0.9371, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2354, root_relative_squared_error: 0.9117,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-BestFirst-CfsSubsetEval-KStar(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9637, f_measure: 0.8946, kappa: 0.7273, kb_relative_information_score: 610.1199, mean_absolute_error: 0.0538, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8954, predictive_accuracy: 0.8976, prior_entropy: 1.2149, recall: 0.8976, relative_absolute_error: 0.4004, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.154, root_relative_squared_error: 0.5966,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Bes ... aceMissingValues-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7846, f_measure: 0.6271, kappa: 0.2903, kb_relative_information_score: 86.8239, mean_absolute_error: 0.1393, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.7401, predictive_accuracy: 0.5913, prior_entropy: 1.2149, recall: 0.5913, relative_absolute_error: 1.0374, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2875, root_relative_squared_error: 1.1134,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ran ... aceMissingValues-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8688, f_measure: 0.7708, kappa: 0.5161, kb_relative_information_score: 308.1807, mean_absolute_error: 0.1044, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8249, predictive_accuracy: 0.755, prior_entropy: 1.2149, recall: 0.755, relative_absolute_error: 0.7772, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2571, root_relative_squared_error: 0.9955,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ranker-ReliefF-KStar(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9852, f_measure: 0.9506, kappa: 0.8765, kb_relative_information_score: 756.1489, mean_absolute_error: 0.0245, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9512, predictive_accuracy: 0.9521, prior_entropy: 1.2149, recall: 0.9521, relative_absolute_error: 0.1822, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1064, root_relative_squared_error: 0.412,
William Raynaut 7 years ago
ran flow weka.kf.Bagging-IBk5(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9646, f_measure: 0.9244, kappa: 0.8098, kb_relative_information_score: 714.3087, mean_absolute_error: 0.0295, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9323, predictive_accuracy: 0.931, prior_entropy: 1.2149, recall: 0.931, relative_absolute_error: 0.22, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.5005,
William Raynaut 7 years ago
ran flow weka.kf.Bagging-SMO(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8869, f_measure: 0.8803, kappa: 0.7032, kb_relative_information_score: -472.5467, mean_absolute_error: 0.2251, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.882, predictive_accuracy: 0.8931, prior_entropy: 1.2149, recall: 0.8931, relative_absolute_error: 1.6762, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.3134, root_relative_squared_error: 1.2139,
William Raynaut 7 years ago
ran flow weka.kf.Bagging-J48(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9851, f_measure: 0.9351, kappa: 0.8378, kb_relative_information_score: 679.0712, mean_absolute_error: 0.0422, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9364, predictive_accuracy: 0.9376, prior_entropy: 1.2149, recall: 0.9376, relative_absolute_error: 0.3142, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1269, root_relative_squared_error: 0.4914,
William Raynaut 7 years ago
ran flow weka.kf.RandomSubspace(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9755, f_measure: 0.8134, kappa: 0.5092, kb_relative_information_score: 481.2696, mean_absolute_error: 0.0846, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8719, predictive_accuracy: 0.8508, prior_entropy: 1.2149, recall: 0.8508, relative_absolute_error: 0.6301, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1781, root_relative_squared_error: 0.6898,
William Raynaut 7 years ago
ran flow weka.kf.ZeroR(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4915, f_measure: 0.6587, kb_relative_information_score: -1.2439, mean_absolute_error: 0.1344, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.5802, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ran ... er-ReliefF-Standardize-IBk5(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9865, f_measure: 0.9426, kappa: 0.8571, kb_relative_information_score: 764.4778, mean_absolute_error: 0.0206, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9457, predictive_accuracy: 0.9454, prior_entropy: 1.2149, recall: 0.9454, relative_absolute_error: 0.1531, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1129, root_relative_squared_error: 0.4373,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ran ... r-InfoGain-Standardize-IBk5(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9412, f_measure: 0.8774, kappa: 0.6959, kb_relative_information_score: 609.3212, mean_absolute_error: 0.0493, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8816, predictive_accuracy: 0.8753, prior_entropy: 1.2149, recall: 0.8753, relative_absolute_error: 0.367, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1702, root_relative_squared_error: 0.6591,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Bes ... SubsetEval-Standardize-IBk5(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9673, f_measure: 0.9181, kappa: 0.801, kb_relative_information_score: 663.1463, mean_absolute_error: 0.0385, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9236, predictive_accuracy: 0.9165, prior_entropy: 1.2149, recall: 0.9165, relative_absolute_error: 0.2866, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1455, root_relative_squared_error: 0.5636,
William Raynaut 7 years ago
ran flow weka.kf.ReplaceMissingValues-PKIDiscretize-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9805, f_measure: 0.9253, kappa: 0.8175, kb_relative_information_score: 687.2145, mean_absolute_error: 0.0371, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9308, predictive_accuracy: 0.9232, prior_entropy: 1.2149, recall: 0.9232, relative_absolute_error: 0.2762, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1331, root_relative_squared_error: 0.5155,
William Raynaut 7 years ago
ran flow weka.kf.AdaBoostM1-SMO(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.954, f_measure: 0.8899, kappa: 0.7211, kb_relative_information_score: 615.2232, mean_absolute_error: 0.0468, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.889, predictive_accuracy: 0.8931, prior_entropy: 1.2149, recall: 0.8931, relative_absolute_error: 0.3488, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1557, root_relative_squared_error: 0.6031,
William Raynaut 7 years ago
ran flow weka.kf.ReplaceMissingValues-J48(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9842, f_measure: 0.9471, kappa: 0.8692, kb_relative_information_score: 759.0542, mean_absolute_error: 0.0221, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9484, predictive_accuracy: 0.9477, prior_entropy: 1.2149, recall: 0.9477, relative_absolute_error: 0.1646, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1192, root_relative_squared_error: 0.4617,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ran ... aceMissingValues-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.907, f_measure: 0.6425, kappa: 0.4163, kb_relative_information_score: 181.2066, mean_absolute_error: 0.1249, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8482, predictive_accuracy: 0.6192, prior_entropy: 1.2149, recall: 0.6192, relative_absolute_error: 0.9296, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.3064, root_relative_squared_error: 1.1867,
William Raynaut 7 years ago
ran flow weka.kf.Standardize-J48(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9679, f_measure: 0.9096, kappa: 0.772, kb_relative_information_score: 650.1972, mean_absolute_error: 0.0437, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9097, predictive_accuracy: 0.912, prior_entropy: 1.2149, recall: 0.912, relative_absolute_error: 0.3255, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1461, root_relative_squared_error: 0.5659,
William Raynaut 7 years ago
ran flow weka.kf.ReplaceMissingValues-Standardize-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9062, f_measure: 0.6571, kappa: 0.427, kb_relative_information_score: 196.118, mean_absolute_error: 0.1216, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8469, predictive_accuracy: 0.6325, prior_entropy: 1.2149, recall: 0.6325, relative_absolute_error: 0.9054, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.3023, root_relative_squared_error: 1.1708,
William Raynaut 7 years ago
ran flow weka.kf.RandomForest(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9884, f_measure: 0.9443, kappa: 0.8608, kb_relative_information_score: 699.4785, mean_absolute_error: 0.0395, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.9444, predictive_accuracy: 0.9443, prior_entropy: 1.2149, recall: 0.9443, relative_absolute_error: 0.2939, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1179, root_relative_squared_error: 0.4565,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ranker-ReliefF-SMO(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8077, f_measure: 0.8419, kappa: 0.6153, kb_relative_information_score: -475.3231, mean_absolute_error: 0.2256, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8428, predictive_accuracy: 0.8541, prior_entropy: 1.2149, recall: 0.8541, relative_absolute_error: 1.6797, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.3157, root_relative_squared_error: 1.2226,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-Ranker-InfoGain-SMO(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7288, f_measure: 0.7756, kappa: 0.4299, kb_relative_information_score: -488.0745, mean_absolute_error: 0.227, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.7682, predictive_accuracy: 0.7906, prior_entropy: 1.2149, recall: 0.7906, relative_absolute_error: 1.6905, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.318, root_relative_squared_error: 1.2315,
William Raynaut 7 years ago
ran flow weka.kf.AttributeSelection-BestFirst-CfsSubsetEval-SMO(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6728, f_measure: 0.7434, kappa: 0.3199, kb_relative_information_score: -494.3159, mean_absolute_error: 0.2269, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.7142, predictive_accuracy: 0.7973, prior_entropy: 1.2149, recall: 0.7973, relative_absolute_error: 1.6896, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.3178, root_relative_squared_error: 1.2307,
William Raynaut 7 years ago
ran flow weka.kf.Bagging-NaiveBayes(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9489, f_measure: 0.7987, kappa: 0.5935, kb_relative_information_score: 416.1641, mean_absolute_error: 0.0828, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8765, predictive_accuracy: 0.7817, prior_entropy: 1.2149, recall: 0.7817, relative_absolute_error: 0.6162, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2242, root_relative_squared_error: 0.8683,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9031, f_measure: 0.8305, kappa: 0.536, kb_relative_information_score: 449.9578, mean_absolute_error: 0.0775, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8473, predictive_accuracy: 0.8497, prior_entropy: 1.2149, recall: 0.8497, relative_absolute_error: 0.5771, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.7495,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8277, f_measure: 0.82, kappa: 0.5057, kb_relative_information_score: 375.4467, mean_absolute_error: 0.0849, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8567, predictive_accuracy: 0.8474, prior_entropy: 1.2149, recall: 0.8474, relative_absolute_error: 0.6318, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2047, root_relative_squared_error: 0.7928,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8531, kappa: 0.5711, kb_relative_information_score: 399.4147, mean_absolute_error: 0.0836, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.8486, prior_entropy: 1.2149, recall: 0.8486, relative_absolute_error: 0.6223, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2023, root_relative_squared_error: 0.7833,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5256, kb_relative_information_score: 3.7822, mean_absolute_error: 0.1335, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9941, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 0.9998,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8475, f_measure: 0.8171, kappa: 0.504, kb_relative_information_score: 370.2974, mean_absolute_error: 0.0893, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.843, predictive_accuracy: 0.8419, prior_entropy: 1.2149, recall: 0.8419, relative_absolute_error: 0.665, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2078, root_relative_squared_error: 0.8048,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8592, f_measure: 0.8304, kappa: 0.5355, kb_relative_information_score: 410.9143, mean_absolute_error: 0.0818, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8439, predictive_accuracy: 0.8474, prior_entropy: 1.2149, recall: 0.8474, relative_absolute_error: 0.6091, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2009, root_relative_squared_error: 0.7782,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8922, f_measure: 0.8359, kappa: 0.554, kb_relative_information_score: 390.7866, mean_absolute_error: 0.0887, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8527, predictive_accuracy: 0.8541, prior_entropy: 1.2149, recall: 0.8541, relative_absolute_error: 0.6601, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2004, root_relative_squared_error: 0.7761,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8644, f_measure: 0.8573, kappa: 0.6251, kb_relative_information_score: 462.007, mean_absolute_error: 0.0734, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8617, predictive_accuracy: 0.8664, prior_entropy: 1.2149, recall: 0.8664, relative_absolute_error: 0.5462, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1912, root_relative_squared_error: 0.7403,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8514, f_measure: 0.8395, kappa: 0.5701, kb_relative_information_score: 435.8522, mean_absolute_error: 0.0752, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8587, predictive_accuracy: 0.8575, prior_entropy: 1.2149, recall: 0.8575, relative_absolute_error: 0.56, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1956, root_relative_squared_error: 0.7574,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4949, kb_relative_information_score: 3.7811, mean_absolute_error: 0.1335, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9936, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4915, kb_relative_information_score: 3.951, mean_absolute_error: 0.1334, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9933, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8586, f_measure: 0.8334, kappa: 0.5486, kb_relative_information_score: 419.0963, mean_absolute_error: 0.0791, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8513, predictive_accuracy: 0.8519, prior_entropy: 1.2149, recall: 0.8519, relative_absolute_error: 0.5889, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1967, root_relative_squared_error: 0.7617,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9046, f_measure: 0.8545, kappa: 0.6066, kb_relative_information_score: 449.2223, mean_absolute_error: 0.0781, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8643, predictive_accuracy: 0.8664, prior_entropy: 1.2149, recall: 0.8664, relative_absolute_error: 0.5812, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1936, root_relative_squared_error: 0.7498,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8344, f_measure: 0.8175, kappa: 0.504, kb_relative_information_score: 366.9094, mean_absolute_error: 0.0855, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8487, predictive_accuracy: 0.843, prior_entropy: 1.2149, recall: 0.843, relative_absolute_error: 0.6368, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2081, root_relative_squared_error: 0.8059,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4915, kb_relative_information_score: 3.951, mean_absolute_error: 0.1334, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9933, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8399, f_measure: 0.8545, kappa: 0.6166, kb_relative_information_score: 439.7043, mean_absolute_error: 0.0765, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8604, predictive_accuracy: 0.8653, prior_entropy: 1.2149, recall: 0.8653, relative_absolute_error: 0.5696, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1968, root_relative_squared_error: 0.7622,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5639, kb_relative_information_score: -18.7893, mean_absolute_error: 0.1354, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 1.0081, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2573, root_relative_squared_error: 0.9964,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5796, kappa: -0.0016, kb_relative_information_score: -16.8963, mean_absolute_error: 0.1348, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7606, prior_entropy: 1.2149, recall: 0.7606, relative_absolute_error: 1.0039, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2574, root_relative_squared_error: 0.9967,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7793, f_measure: 0.8108, kappa: 0.4799, kb_relative_information_score: 340.2593, mean_absolute_error: 0.0893, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8472, predictive_accuracy: 0.8419, prior_entropy: 1.2149, recall: 0.8419, relative_absolute_error: 0.665, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2123, root_relative_squared_error: 0.8223,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5815, kappa: -0.0013, kb_relative_information_score: -1.7105, mean_absolute_error: 0.1327, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7606, prior_entropy: 1.2149, recall: 0.7606, relative_absolute_error: 0.9881, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2569, root_relative_squared_error: 0.9951,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5791, kappa: -0.0016, kb_relative_information_score: -20.5132, mean_absolute_error: 0.1346, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7606, prior_entropy: 1.2149, recall: 0.7606, relative_absolute_error: 1.0021, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2572, root_relative_squared_error: 0.9959,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.521, kappa: -0.0079, kb_relative_information_score: 7.1123, mean_absolute_error: 0.133, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.755, prior_entropy: 1.2149, recall: 0.755, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.261, root_relative_squared_error: 1.0107,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9057, f_measure: 0.8289, kappa: 0.5315, kb_relative_information_score: 440.8985, mean_absolute_error: 0.0802, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8458, predictive_accuracy: 0.8486, prior_entropy: 1.2149, recall: 0.8486, relative_absolute_error: 0.5973, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1957, root_relative_squared_error: 0.7579,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7256, f_measure: 0.7971, kappa: 0.4395, kb_relative_information_score: 291.1095, mean_absolute_error: 0.0957, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8441, predictive_accuracy: 0.833, prior_entropy: 1.2149, recall: 0.833, relative_absolute_error: 0.7122, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2205, root_relative_squared_error: 0.8541,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, kb_relative_information_score: -6.3848, mean_absolute_error: 0.1328, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9889, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.257, root_relative_squared_error: 0.9951,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8704, f_measure: 0.8511, kappa: 0.5986, kb_relative_information_score: 441.3426, mean_absolute_error: 0.0765, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8588, predictive_accuracy: 0.8619, prior_entropy: 1.2149, recall: 0.8619, relative_absolute_error: 0.5698, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1944, root_relative_squared_error: 0.753,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7018, f_measure: 0.7563, kappa: 0.3104, kb_relative_information_score: 242.7474, mean_absolute_error: 0.1047, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.7914, predictive_accuracy: 0.8018, prior_entropy: 1.2149, recall: 0.8018, relative_absolute_error: 0.7792, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2303, root_relative_squared_error: 0.8919,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8615, f_measure: 0.832, kappa: 0.5502, kb_relative_information_score: 406.1312, mean_absolute_error: 0.0838, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8526, predictive_accuracy: 0.8519, prior_entropy: 1.2149, recall: 0.8519, relative_absolute_error: 0.6242, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2, root_relative_squared_error: 0.7745,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8858, f_measure: 0.8075, kappa: 0.4708, kb_relative_information_score: 416.6547, mean_absolute_error: 0.0835, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8313, predictive_accuracy: 0.8352, prior_entropy: 1.2149, recall: 0.8352, relative_absolute_error: 0.6214, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2, root_relative_squared_error: 0.7747,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8478, f_measure: 0.821, kappa: 0.5031, kb_relative_information_score: 348.0754, mean_absolute_error: 0.0895, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8432, predictive_accuracy: 0.8419, prior_entropy: 1.2149, recall: 0.8419, relative_absolute_error: 0.6663, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2081, root_relative_squared_error: 0.8059,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5468, kb_relative_information_score: 12.6266, mean_absolute_error: 0.1294, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9635, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2573, root_relative_squared_error: 0.9964,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5675, kappa: -0.0016, kb_relative_information_score: -10.1731, mean_absolute_error: 0.1337, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7606, prior_entropy: 1.2149, recall: 0.7606, relative_absolute_error: 0.9959, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2574, root_relative_squared_error: 0.9966,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8561, f_measure: 0.8359, kappa: 0.551, kb_relative_information_score: 404.1681, mean_absolute_error: 0.0837, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8494, predictive_accuracy: 0.8519, prior_entropy: 1.2149, recall: 0.8519, relative_absolute_error: 0.6231, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2018, root_relative_squared_error: 0.7814,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4915, kb_relative_information_score: 3.951, mean_absolute_error: 0.1334, mean_prior_absolute_error: 0.1343, number_of_instances: 898, predictive_accuracy: 0.7617, prior_entropy: 1.2149, recall: 0.7617, relative_absolute_error: 0.9933, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2582, root_relative_squared_error: 1,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.81, f_measure: 0.8222, kappa: 0.513, kb_relative_information_score: 370.5689, mean_absolute_error: 0.0854, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8576, predictive_accuracy: 0.8486, prior_entropy: 1.2149, recall: 0.8486, relative_absolute_error: 0.6356, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2057, root_relative_squared_error: 0.7965,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8613, f_measure: 0.8463, kappa: 0.5973, kb_relative_information_score: 428.1084, mean_absolute_error: 0.0788, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8515, predictive_accuracy: 0.8575, prior_entropy: 1.2149, recall: 0.8575, relative_absolute_error: 0.5865, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1969, root_relative_squared_error: 0.7626,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8401, f_measure: 0.841, kappa: 0.5721, kb_relative_information_score: 443.8002, mean_absolute_error: 0.0745, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8583, predictive_accuracy: 0.8586, prior_entropy: 1.2149, recall: 0.8586, relative_absolute_error: 0.5549, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1929, root_relative_squared_error: 0.747,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.869, f_measure: 0.8415, kappa: 0.5734, kb_relative_information_score: 436.4371, mean_absolute_error: 0.0766, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8568, predictive_accuracy: 0.8575, prior_entropy: 1.2149, recall: 0.8575, relative_absolute_error: 0.5701, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.1937, root_relative_squared_error: 0.7503,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7887, f_measure: 0.7986, kappa: 0.4459, kb_relative_information_score: 294.1103, mean_absolute_error: 0.0956, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8362, predictive_accuracy: 0.8318, prior_entropy: 1.2149, recall: 0.8318, relative_absolute_error: 0.7121, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2198, root_relative_squared_error: 0.8511,
Jan van Rijn 7 years ago
ran flow sklearn.pipeline.Pipeline(impu ... er=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set anneal
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7533, f_measure: 0.7921, kappa: 0.4264, kb_relative_information_score: 287.8934, mean_absolute_error: 0.0962, mean_prior_absolute_error: 0.1343, number_of_instances: 898, precision: 0.8347, predictive_accuracy: 0.8296, prior_entropy: 1.2149, recall: 0.8296, relative_absolute_error: 0.7164, root_mean_prior_squared_error: 0.2582, root_mean_squared_error: 0.2209, root_relative_squared_error: 0.8557,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

estimation_procedure 10-fold Crossvalidation
evaluation_measures predictive_accuracy
source_data anneal (1)
target_feature class

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs