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We combine Forward-backward and Principal Component Analysis for feature reduction. The multi-classifier evaluates three clustering methods and ascertains the best classification methods in each cluster based on some training data. In this study, we use ten datasets taken from Machine Learning Repository datasets of the University of California at Irvine (UCI). The proposed multi-classifier improves both computation time and accuracy as compared with all other classification methods. 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