Optimal SVM parameter selection for non-separable and unbalanced datasets
نویسندگان
چکیده
منابع مشابه
Optimal SVM parameter selection for non-separable and unbalanced datasets.
This article presents a study of three validation metrics used for the selection of optimal parameters of a support vector machine (SVM) classifier in the case of non-separable and unbalanced datasets. This situation is often encountered when the data is obtained experimentally or clinically. The three metrics selected in this work are the area under the ROC curve (AUC), accuracy, and balanced ...
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ژورنال
عنوان ژورنال: Structural and Multidisciplinary Optimization
سال: 2014
ISSN: 1615-147X,1615-1488
DOI: 10.1007/s00158-014-1105-z