Optimized Kernel Entropy Components
نویسندگان
چکیده
منابع مشابه
Kernel Principal Components Are Maximum Entropy Projections
Principal Component Analysis (PCA) is a very well known statistical tool. Kernel PCA is a nonlinear extension to PCA based on the kernel paradigm. In this paper we characterize the projections found by Kernel PCA from a information theoretic perspective. We prove that Kernel PCA provides optimum entropy projections in the input space when the Gaussian kernel is used for the mapping and a sample...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks and Learning Systems
سال: 2017
ISSN: 2162-237X,2162-2388
DOI: 10.1109/tnnls.2016.2530403