The paper proposed a Priori Kernel Principal Component Analysis (PKPCA), which integrates between and within class variances into KPCA, and thus the classification performances can be enhanced.

• 本文提出了一种新的具有先验类别信息的非线性主元分析算法:PKPCA(Priori Kernel Principal Component Analysis),通过将样本类内差和类间差融入总体方差中,从而达到更好的分类目的。