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For Unbalanced Data Set, the KNN (K the nearest neighbor) and SVM (support vector machine) classification algorithm’s prediction result would tend to most class; the misclassification rate of the minority class was big. This paper analyzed in detail the influence of unbalanced data set to KNN and SVM in theory, and proposed a new method to solve this problem. Experiment based on UCI data set using KNN and SVM algorithm to prove the validity of the proposed method. KeywordsUnbalanced Data Set, classify, KNN, SVM

THE RESEARCH OF KNN AND SVM CLASSIFICATION PERFORMANCE ON TWO KINDS OF UNBALANCED DATA SET