关键词: AdaBoost, 支持向量机, 组合分类器, 规则抽样

Abstract: A combined classification algorithm based on improved AdaBoost and Support Vector Machine，is proposed in order to deal with the problems of multiclass classification.Adopt a rule sampling to solve the unbalance of samples in the SVM.Improving the AdaBoost makes it consider the importance of sparse sample distribution at the beginning，this is advantageous to the right demarcation of rare sample.Experiment proves this algorithm can raise the generalization ability compared with the standard SVM.

Key words: AdaBoost, Support Vector Machine（SVM）, combined classification, rule sampling