Abstract: SVM(Support Vector Machine) is an important tool of solving the nonlinear problem. This paper introduces the methods of constructing Support Vector Stepwise Regression speedily ----starting from the Multiple Linear Regression model of the Sample Subset to search the Support Vectors with the aim of decreasing the size of the Kernel Matrix and reducing the computing complexity of Support Vector Stepwise Regression, analyzes the complexity of the algorithm and illustrates an application example.

摘要： 支持向量机是解决非线性问题的重要工具。本文对多元线性回归模型和支持向量机的原始形式进行比较，拟定从样本子集的多元线性回归模型出发，逐步搜索支持向量，提出了一种建立支持向量回归机的快速算法，以降低核矩阵的规模从而降低解凸二次规划的复杂度；最后，分析了该算法的复杂度，并提供了一个算例。