In of attributes are considered and to
One of the maindrawbacks of the standard SVM is that the training process of the SVM issensitive to the outliers or noise in the training dataset due to over fitting. It has beenfound that the performance of fuzzy SVM highly depends on the determination offuzzy memberships therefore in this paper; we proposed a new method β