基于支持向量机分类的回归方法

A Regression Method Based on the Support Vectors for Classification

支持向量机(support vector machine,简称SVM)是一种基于结构风险最小化原理的分类技术,也是一种新的具有很好泛化性能的回归方法.提出了一种将回归问题转化为分类问题的新思想.这种方法具有一定的理论依据,与SVM回归算法相比,其优化问题几何意义清楚明确.

The support vector machine is a classification technique based on the structural risk minimization principle, and it is also a class of regression method with good generalization ability. In this paper, a new idea that each regression problem can be changed into a classification problem is presented. The proposed method has some theoretical foundations. Compared with SVM regression method, the geometric meaning of optimization problem in this paper is very clear and obvious.