摘要
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.
出处
《计算机工程》
CAS
CSCD
北大核心
2005年第12期23-25,共3页
Computer Engineering
关键词
支持向量机
加权支持向量机
分类算法
机器学习
Support vector machines
Weighted support vector machines
Classification algorithm
Machine learning
