H. Sadoghi Yazdi

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The well-known support vector data description (SVDD) is based on precise description of precise data. When we know the features of training samples precisely and we are uncertain about their class labels, the fuzzy SVDD can be used to obtain the data description. But if the features of training samples are fuzzy numbers, the fuzzy SVDD cannot be utilized.(More)
Simple classifiers have the advantage of more generalization capability with the side effect of less power. It would be a good idea if we could build a classifier which is as simple as possible while giving it the ability of classifying complex patterns. In this paper, a hybrid classifier called “constrained classifier” is presented that classifies most of(More)
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