A Support Vector Classifier Based on Vague Similarity Measure

A Support Vector Classifier Based on Vague Similarity Measure

Support vector machine (SVM) is a popular machine learning method for its high generalizaiton ability. How to find the adaptive kernel function is a key problem to SVM from theory to practical applications. This paper proposes a support vector classifer based on vague sigmoid kernel and its similari...

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Main Authors: Yong Zhang, Jing Cai
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/928054
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spelling doaj-9f93344107754568be810864c3b973292020-11-24T22:35:41ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/928054928054A Support Vector Classifier Based on Vague Similarity MeasureYong Zhang0Jing Cai1School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, Dalian, Liaoning Province 116081, ChinaSchool of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, Dalian, Liaoning Province 116081, ChinaSupport vector machine (SVM) is a popular machine learning method for its high generalizaiton ability. How to find the adaptive kernel function is a key problem to SVM from theory to practical applications. This paper proposes a support vector classifer based on vague sigmoid kernel and its similarity measure. The proposed method uses the characteristic of vague set, and replaces the traditional inner product with vague similarity measure between training samples. The experimental results show that the proposed method can reduce the CPU time and maintain the classification accuracy.http://dx.doi.org/10.1155/2013/928054
collection DOAJ
language English
format Article
sources DOAJ
author Yong Zhang
Jing Cai
spellingShingle Yong Zhang
Jing Cai
A Support Vector Classifier Based on Vague Similarity Measure
Mathematical Problems in Engineering
author_facet Yong Zhang
Jing Cai
author_sort Yong Zhang
title A Support Vector Classifier Based on Vague Similarity Measure
title_short A Support Vector Classifier Based on Vague Similarity Measure
title_full A Support Vector Classifier Based on Vague Similarity Measure
title_fullStr A Support Vector Classifier Based on Vague Similarity Measure
title_full_unstemmed A Support Vector Classifier Based on Vague Similarity Measure
title_sort support vector classifier based on vague similarity measure
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description Support vector machine (SVM) is a popular machine learning method for its high generalizaiton ability. How to find the adaptive kernel function is a key problem to SVM from theory to practical applications. This paper proposes a support vector classifer based on vague sigmoid kernel and its similarity measure. The proposed method uses the characteristic of vague set, and replaces the traditional inner product with vague similarity measure between training samples. The experimental results show that the proposed method can reduce the CPU time and maintain the classification accuracy.
url http://dx.doi.org/10.1155/2013/928054
work_keys_str_mv AT yongzhang asupportvectorclassifierbasedonvaguesimilaritymeasure
AT jingcai asupportvectorclassifierbasedonvaguesimilaritymeasure
AT yongzhang supportvectorclassifierbasedonvaguesimilaritymeasure
AT jingcai supportvectorclassifierbasedonvaguesimilaritymeasure
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