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This paper presents an effective feature selection method for support vector machine (SVM). Unlike the traditional combinatorial searching method, feature selection is translated into the model selection of SVM which has been well studied. In more detail, the basic idea of this method is to tune the parameters of the Gaussian ARD (Automatic Relevance Determination) kernel via optimization of kernel...
In this paper we present a method of functionally classifying malicious code that might lead to automated attacks and intrusions using kernel machines. We study the performance of kernel methods in the context of robustness and generalization capabilities of malware classification. Current static detection and scanning techniques for malicious code and malware have serious limitations; on the other...
Microarray is an important tool in gene analysis research. It can help identify genes that might cause various cancers. In this paper, we use feature selection methods and the support vector machine (SVM) to search for the disease-causing genes in microarray data of three different cancers. The feature selection methods are based on Euclidian distance (ED) and Pearson correlation coefficient(PCC)...
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