关键词: 监督学习, 最小二乘支撑向量机, 优化算法

Abstract: To solve the problem that the optimization of Least Square Support Vector Machine (LSSVM) consumes too much time, a new method called Newton-LSSVM, which used Newton optimization to solve the optimization problem of LSSVM, was proposed. The method first converted LSSVM to unconstrained optimization, and then used Newton optimization to solve the optimization problem iteratively. The experimental results show that Newton-LSSVM can reduce the training time greatly but do not decrease the generating ability of LSSVM.

Key words: supervised learning, Least Square Support Vector Machine (LSSVM), optimization algorithm