Title: An improved algorithm of local support vector machine
Abstract: Local support vector machine is a widely used classifier. It has been attracting more and more attention both on its theoretical research and practical applications. Nowadays, there exists a problem in many traditional local support vector machine algorithms: the imbalance of the number of the samples leads to the difficulty in improving the classification accuracy. In this paper, firstly, under the inspiration of weighted support vector machine, the algorithm named WFalk-SVM is proposed, which uses weight in Falk-SVM. Secondly, the experiments demonstrates the feasibility and effectiveness. At last, we conclude the weighted Falk-SVM.
Publication Year: 2013
Publication Date: 2013-01-01
Language: en
Type: article
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