Balanced Fuzzy Support Vector Machine Based on Imbalanced Data Set

In view of the classification of imbalance data set with the larger imbalanced ratio of class,a balanced fuzzy support vector machine(BFSVM) was proposed,making use of the imbalance adjustment factor and the fuzzy membership based on the features of sample points.Firstly,it computes the sample covariance matrix and gets the imbalance adjustment factor,then computes the fuzzy membership of every sample and gets the contribution rate of every sample.Fuzzy membership and imbalance adjustment affect the sample error of classifier at the same time.The experiment results prove that the algorithm has a good effect on the larger imbalanced ratio.