Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Science & Technology Vision》 2016-23
Add to Favorite Get Latest Update

The Research of the Fuzzy-Binary tree Support Vector Machines

ZHANG Jia-jian;Shandong University of Science and Technology;  
The support vector machine algorithm based on statistical learning theory is a new kind of machine learning algorithm proposed by Vapnik et al, Because of its excellent learning performance, especially the generalization ability, it has aroused great concern in this field. Traditional support vector machine is to do two yuan classification, and more in fact is a multi class classification. Existing multi class classification method, the binary tree support vector machine overall performance is better than that of "a", "a pair of many" other multi class classification method, but binary tree support vector machine due to the presence of "error accumulation" problem, the classification accuracy rate is low. In this paper, for binary tree support vector machine classification accuracy lower shortcomings, fuzzy support vector machine and the binary tree support vector machine and the fuzzy techniques are applied to support vector machine, so as to improve the classification accuracy.
【CateGory Index】: TP18
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved