关键词: 遗传算法, 对支持向量机, 分类和预测

Abstract: Aiming at the fuzzy problem in Multi-class Twin Support Vector Machine（Multi-TWSVM）, a new method of Decision Tree Twin Support Vector Machine based on Genetic Algorithm（GA-DTTSVM） is proposed. GA-DTTSVM builds the decision tree with the feature data by genetic algorithm to separate the fuzzy region of samples, so that the sample recognition rate can be improved. For each node of the decision tree this paper uses the Twin Support Vector Machine （TWSVM） to train a classifier, and finally it uses the trained classifier for classification and prediction. The experiments show that GA-DTTSVM algorithm can get higher classification accuracy and faster training speed compared with Decision Tree Twin Support Vector Machine algorithm（DTTSVM） and Multi-TWSVM.

Key words: genetic algorithm, twin support vector machine, classification and prediction