Pengarang

Ismail Djakaria

Subjek

- Sains

Abstrak

This paper purpose to examine the kernel principal component regression (KPCR), which is the development of the principal component regression (PCR) with the radial basis fungction (RBF) kernel or Gaussian kernel. This study started to presented a standard principal component analysis (PCA) and kernel principal component analysis (KPCA), that includes PCA in feature space and KPCA in input space. The focus of this study describes the properties of model KPCR published in several theorems, includes linear estimator, unbiased estimator, and the best estimator, that known the best linear unbiased estimator (BLUE). Key words: PCR model, KPCR model, RBF kernel, the BLUE.

Penerbit

International Journal of Academic Research

Kontributor

-

Terbit

2015

Tipe Material

ARTIKEL

Right

Baku, Azerbaijan: Progress