Title :
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.
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;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258838
