关键词: Fisher准则, 组合核, 多核, 核参数, 支持向量机

Abstract: For the contradiction between time and performance in the modeling of combined-kernel support vector machines，it proposes a new scheme in finding the ideal compromise of performance and time.Kernels’combination is studied beneficial for learning and generalization ability，as well as the method of optimizing kernels’parameters.A master-slave kernel phase-optimized programs is proposed，namely a time optimizes parameters of one kernel，and gradually adds other sub-kernel.Time cost is the simple sum of time every single-kernel modeling consumed.Compared with the evolutionary algorithm，time consumed is less，and compared with the partition algorithm，the performance is better.The proposed scheme in terms of time and performance achieves good results.

Key words: Fisher, combined kernel, multi-kernel, kernel parameters, support vector machines