EXTERNAL VS. INTERNAL SVM-RFE: THE SVM-RFE METHOD REVISITED AND APPLIED TO EMOTION RECOGNITION
نویسندگان
چکیده
منابع مشابه
A Novel SVM-RFE for Gene Selection∗
Selecting a subset of informative genes frommicroarray expression data is a critical data preparation step in cancer classification and other biological function analysis. The support vector machine recursive feature elimination (SVM-RFE) is one of the most effective feature selection method which has been successfully used in selecting informative genes for cancer classification. While, the SV...
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Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatolo...
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Feature selection is an important topic in bioinformatics. Defining informative features from complex high dimensional biological data is critical in disease study, drug development, etc. Support vector machine-recursive feature elimination (SVM-RFE) is an efficient feature selection technique that has shown its power in many applications. It ranks the features according to the recursive featur...
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ژورنال
عنوان ژورنال: Neural Network World
سال: 2015
ISSN: 1210-0552,2336-4335
DOI: 10.14311/nnw.2015.25.004