KARYA ILMIAH

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
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