计算机工程与应用2017，Vol.53Issue(6)：236-240,270,6.DOI:10.3778/j.issn.1002-8331.1508-0166
基于回归树的支持向量机规则提取及应用
Rule extraction of support vector machine based on regres- sion tree and application
摘要
Abstract
The kernel function of Support Vector Machine(SVM)used of inner product causes"black box"problem. Cur-rently, the research of"black box"mainly adopts the rule extraction method to solve classification problems, but the problem of the regression is rarely mentioned. This paper tries to propose an SVM regression rule extraction method based on the regression tree algorithm. The algorithm takes full advantage of the special properties of support vectors and the advantage of the regression tree, establishes tree model based on support vectors. It successfully extracts high decision-making capacity, including less variables, a small amount of calculation and easy to read rules. Through training and testing the standard data set"Auto MPG"and the actual production data of coal to methanol, comparison of results with other algorithms shows that, the extracted regression rules in the training accuracy and prediction accuracy have a certain degree of improvement.关键词
支持向量机/规则提取/回归树Key words
support vector machine/rules extraction/regression tree分类
信息技术与安全科学引用本文复制引用
王建国,董泽宇,张文兴,卢丹..基于回归树的支持向量机规则提取及应用[J].计算机工程与应用,2017,53(6):236-240,270,6.基金项目
国家自然科学基金(No.21366017) （No.21366017）
内蒙古科技大学大学生科技创新基金资助项目(No.2014060). （No.2014060）
