Support Vector Machine for Classification Based on Fuzzy Training Data

Author

Ji, Ai-bing ; Pang, Jia-hong ; Li, Shu-huan ; Sun, Jian-ping

Author_Institution

Coll. of Medicine, Hebei Univ.

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

1609

Lastpage

1614

Abstract

Support vector machines (SVMs) have been very successful in pattern recognition and function estimation problems, but in the support vector machines for classification, the training examples are non-fuzzy input and output is y=plusmn1;. In this paper, we introduce the support vector machine in which the training examples are fuzzy input, and give some solving procedure of the support vector machine with fuzzy training data

Keywords

fuzzy set theory; learning (artificial intelligence); pattern classification; support vector machines; SVM; function estimation; fuzzy training data; pattern classification; pattern recognition; support vector machine; Cybernetics; Educational institutions; Electronic mail; Linear programming; Machine learning; Pattern recognition; Quadratic programming; Sun; Support vector machine classification; Support vector machines; Training data; Support vector machine; fuzzy chance constraint programming; fuzzy linear separable example; fuzzy training examples; possibility measure;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258838

Filename

4028322

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2890529