关键词:

支持向量机, 多类分类, 模糊核, 二叉树

Abstract:

Traditional support vector machines (SVM) is originally designed for binary classification.How to effectively extend it to multi-class classification is worthy to research. This paper compared some common support vector machines for multi-class classification problems, and proposed a multi-class support vector machine based on fuzzy kernel clustering algorithm.The classification accuracy and classification speed of support vector machine depended on the tree structure.This multi-class support vector machine used fuzzy kernel clustering algorithm to generated fuzzy class, and combined with the multi-class SVM based on binary tree classification algorithm for multi-class classification.Experimental results showed that the proposed method was more effective and accurate.

Key words:

支持向量机, 多类分类, 模糊核, 二叉树