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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Veröffentlicht in:	Industrial Engineering & Management Systems Jg. 11; H. 1; S. 26 - 29
Hauptverfasser:	Ha, Ming-Hu, Huang, Jia-Ying, Yang, Yang, Wang, Chao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	대한산업공학회 01.03.2012
Schlagworte:	산업공학 Type-2 Fuzzy Training Samples Fuzzy Chance-Constrained Programming Support Vector Machine Mean Reduction Method
ISSN:	1598-7248, 2234-6473
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	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
Bibliographie:	G704-002162.2012.11.1.015
ISSN:	1598-7248 2234-6473
DOI:	10.7232/iems.2012.11.1.026