摘要
针对直接多类分类方法,提出了一种新的基于直接构造多类SVM分类器的模糊多类支持向量机算法FCS-SVM。在算法中,重构了优化问题及其约束条件,以及Lagrange公式,并进行了推导。通过在标准数据集上的几个实验,对这些算法进行了比较分析。实验结果表明提出的算法可以得到比较理想的分类精度。
This paper presents a novel direct constructing-based fuzzy multi-class support vector classifier,named as FCS-SVM,based on previous multi-class classification method by Crammer and Singer.This algorithm,the optimal problem and its constraints of multi-class classification are reconstructed,and its corresponding Lagrangian formula is re-deduced.Experimental comparison with the previous work indicates that the method can obtain better classification ratio.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第8期12-15,共4页
Computer Engineering and Applications
基金
国家中小企业创新基金(No.05C26212120357)
关键词
支持向量机
模糊
多类分类
Support Vector Machine
fuzzy
multi-class classification
