关键词: 支持向量数据域描述，模糊隶属度，模糊支持向量机，平衡模糊支持向量机，不平衡因子

Abstract: In view of the classification of imbalance data set with the larger unbalanced 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 resups prove that the algorithm has a good effect on the larger unbalanced ratio.

Key words: Support vector data description, Fuzzy membership, Fuzzy support vector machine, Balanced fuzzy support vector machine,Imbalanced factor