一种加权支持向量机分类算法

A Weighted Support Vector Classification Algorithm

提出了一种加权C-SVM分类算法,并从理论上分析了算法的性能。该算法通过引入类权重因子和样本权重因子实现了类加权和样本加权两种功能。实验结果表明,该算法可以有效地解决由类大小不均衡引发的分类错误问题以及重要样本的错分问题。

This paper proposes a weighted C-SVM algorithm and analyzes its classification performance theoretically. This weighted C-SVMintroduces weight factors for classes and samples. Experiments show that C-SVM can effectively solve the misclassification problem resulted fromthe imbalance in the number of training samples of different classes and the problem that important samples are misclassified.