Research of algorithm on support vector stepwise regression and its application

被引：0

作者：

Zeng, Shaohua ^{[1
]}

Wei, Yan ^{[1
]}

He, Yi ^{[1
]}

Cao, Changxiu ^{[1
]}

机构：

[1] Chongqing Univ, Dept Automat, Chongqing 630044, Peoples R China

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE: 50 YEARS' ACHIEVEMENTS, FUTURE DIRECTIONS AND SOCIAL IMPACTS | 2006年

关键词：

support vector stepwise regression; kerne lmatri; algorithm; the complexity analysis;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

SVM(Support Vector machine) is an important tool of solving the nonlinear problem. This paper introduces the methods of constructing Support Vector Stepwise Regression ---- starting from the center of the sample set to search the Support Vectors. It provides a speedy algorithm of Support Vector Stepwise Regression with the aim of decreasing the size of the Kernel Matrix and reducing the computing complexity of Support Vector Stepwise Regression, and analyzes the complexity of the algorithm and illustrates an, application example.

引用

页码：720 / 724

页数：5

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