Support Vector Machine Based on Type-2 Fuzzy Training Samples

In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2...

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Vydané v:Industrial Engineering & Management Systems Ročník 11; číslo 1; s. 26 - 29
Hlavní autori: Ha, Ming-Hu, Huang, Jia-Ying, Yang, Yang, Wang, Chao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 대한산업공학회 01.03.2012
Predmet:
산업공학
Type-2 Fuzzy Training Samples
Fuzzy Chance-Constrained Programming
Support Vector Machine
Mean Reduction Method
ISSN:1598-7248, 2234-6473
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Shrnutí:In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2 fuzzy samples on generalized credibility space is introduced. Further, by utilizing fuzzy chance-constrained programming and classic support vector machine, a support vector machine based on type-2 fuzzy training samples and established on generalized credibility space is given. An example shows the efficiency of the support vector machine. KCI Citation Count: 0
Bibliografia:G704-002162.2012.11.1.015
ISSN:1598-7248
2234-6473
DOI:10.7232/iems.2012.11.1.026