Fast Weighted Support Vector Machine Training Algorithm
一种快速加权支持向量机训练算法

This paper proposed a new traning algorithm of W-SVM that uses second-order information of objective function to select working set and deduced its KKT optimization condition.The experimental results show that the algorithm reduces the number of iterations,comparing with the training algorithm that uses first-order approximate information of objective function to select working set,especially when the training set is very large,its convergence rate is speeded up highly.