关键词: 支持向量机, 类增量学习, 分类算法, 加权

Abstract: In order to solve the misclassification problem resulted from the imbalance of the number of training samples of different classes in the process of class-incremental learning for support vector machine，presents a weighted class-incremental learning algorithm.It uses one against rest training method to construct a new binary classifier takes all the samples from known classes as negative and that of the new class as positive，also introduces weight factors for classes according to the proportion of the training samples，which can effectively improve the classification accuracy of class that has fewer samples.The experiment shows that the result of this method is effective.

Key words: Support Vector Machines（SVM）, class-incremental learning, classification algorithm, weight