Incremental PSVM learning algorithm based on cloud model
基于云模型的最接近支持向量机增量学习方法*

Aiming at the limitations of incremental learning in classical SVM, an incremental PSVM learning algorithm based on cloud model is proposed in this paper. The fast learning ability of PSVM is employed to yield the initial classification hyperplane, and then, all training datasets are reduced by using k-NN method and the plane. After that, we utilize cloud model to directly discriminate analysis on the reduced dataset. The simple algorithm, with less computational time and better anti-noise ability, could well embody the distribution of incremental samples and can be solved without iteration. Experiment results show that the algorithm could not only keep well classification accuracy and generalization ability, but also improve the training speed.