KECA_Journal_Article

代码说明：

说明：  Robert Jenssen 撰写论文原文(We introduce kernel entropy component analysis (kernel ECA) as a new method for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated via a kernel matrix using Parzen windowing. This is achieved by projections onto a subset of entropy preserving kernel principal component analysis (kernel PCA) axes)

文件列表：

Kernel Entropy Component Analysis_Robert Jenssen .pdf, 1287585 , 2019-01-03