Study on Support Vector Machine Based Decision Tree and Application

被引：5
|
作者：
Dong, G. M. [1 ]
Chen, J. [1 ]
机构：
[1] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai, Peoples R China
来源：
FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 5, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/FSKD.2008.252
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Data mining has many topics such as classification, clustering, association, prediction, etc. Recently, classification problem is the research hotspot and decision tree is one of the most widely used classification methods, where C4.5 is one favorite algorithm. According to the disadvantages of conventional support vector machine(SVM), a SVM based decision tree (SVMDT) is introduced and modified by using equivalent distance as the class separability measure and including the consideration of "local class cluster" problem. At last the modified SVMDT is used to make diagnosis analysis of an experimental rotor kit.
引用
收藏
页码：318 / 322
页数：5
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