关键词: 核主成分分析, 汇特征空间, 遗传算法

Abstract: Kernel principal component analysis can extract the nonlinear features of the data, but the performance is great impacted by the parameter of kernel function. This paper presents a kernel parameters optimization method which based on a piecewise binary encoding. The experimental results are very good by using the approach to optimize the kernel parameters in the case of unknown the distribution of the data, which indicating the effectiveness of the method.

Key words: kernel principal components analysis, feature spaces, genetic algorithm