Sensitivity/specificity on the training and testing sets for different classification models with the optimal parameter combination.
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https://figshare.com/articles/dataset/_Sensitivity_specificity_on_the_training_and_testing_sets_for_different_classification_models_with_the_optimal_parameter_combination_/1227873
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“▴” denotes that a p-value of <0.001 was obtained by ANOVA between F-score_FDA and F-score_SVM; “*” denotes that a p-value of <0.001 was obtained by ANOVA between F-score_BPNN and F-score_SVM; for BPNN, the number of hidden nodes = 5, and the learning rate = 0.03; for SVM, radial = 32, and penalty parameter C = 28.
Sensitivity/specificity on the training and testing sets for different classification models with the optimal parameter combination.
创建时间：
2014-11-03
