信息与控制2016，Vol.45Issue(4)：444-448,455,6.DOI:10.13976/j.cnki.xk.2016.0444
一种向量预选取的分段支持向量机回归算法
Vector Pre-selected Piecewise Regression Algorithm for Support Vector Machines
杨海涛 1肖军 1王佩瑶1
作者信息
- 1. 辽宁石油化工大学信息与控制工程学院，辽宁抚顺 113001
- 折叠
摘要
Abstract
When data is volatile,the specific set of regression parameters of the traditional support vector machine cannot meet the requirement for the parameters to change with the data distribution.This results in the regres-sion curve not meeting the precision requirements.At the same time,we wanted to remove some of the nones-sential data in the regression process to speed up the problem-solving process.To address the above two prob-lems,in this paper,we present a vector pre-selected piecewise regression algorithm for a support vector ma-chine (p-p-SVR).First,the algorithm deletes some unnecessary data,based on their spatial distribution. Next,based on the complexity of different regions of the sample,training data are divided into several do-mains,and corresponding parameters are set for each region.Simulation results show that,compared with the traditional method,the p-p-SVR algorithm has better regression accuracy and generalization performance.关键词
支持向量机/回归/分段/向量预选Key words
support vector machine/regression/piecewise/vector pre-selected分类
信息技术与安全科学引用本文复制引用
杨海涛,肖军,王佩瑶..一种向量预选取的分段支持向量机回归算法[J].信息与控制,2016,45(4):444-448,455,6.
