Kernel Principal Component Analysis Algorithm
(Redirected from kernel PCA)
A Kernel Principal Component Analysis Algorithm is a PCA algorithm that is a kernel-based algorithm.
- AKA: Kernel PCA.
- See: Multivariate Statistics, Reproducing Kernel Hilbert Space, Principal Component Analysis, Kernel Methods.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Kernel_principal_component_analysis Retrieved:2015-2-9.
- In the field of multivariate statistics, kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non-linear mapping.