摘要
支持向量机是一种新型机器学习方法,由于其出色的学习性能,该技术已成为机器学习领域新的研究热点。介绍用于分类的支持向量机的统计学习理论基础,在此基础上提出了支持向量机的分类算法,讨论了支持向量机存在的问题,对用于分类的支持向量机的应用前景进行了展望。
Support veCtor machines are a kind of novel machine learning method, which have become the hotspot of machine learning because of their excellent performance. In this paper, the elements of statistical learning theory for support vector machines used in classification and algorithms are introduced. The main issues of support vector machine are discussed, and the application foreground of support vector machine is prospected.
出处
《计算机技术与发展》
2006年第11期56-58,共3页
Computer Technology and Development
基金
中国石油大学科技创新基金资助(05C088)
关键词
支持向量机
统计学习理论
结构风险最小化
数据分类
support vector machine
statistical learning theory
structural risk minimization
data clasification