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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 12 | Page No.: 2313-2318
DOI: 10.3923/jas.2009.2313.2318
 
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Improved Evolving Kernel of Fisher’s Discriminant Analysis for Classification Problem

Hanaa E. Sayed, Hossam A. Gabbar and Shigeji Miyazaki

Abstract:
This study presents a kernel approach called Improved Evolving Kernel Fisher’s Discriminant Analysis (IE-KFDA), which chooses kernel function parameters using proposed Gaussian mutation operator. Evolutionary Programming (EP) known by enhancing the search performance without increasing the computational time. An integration of KFDA with evolutionary optimization algorithm is presented. Classification example shows improving classification results using IE-KFDA in classifying different groups of data over KFDA, KPCA and PLS.
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How to cite this article:

Hanaa E. Sayed, Hossam A. Gabbar and Shigeji Miyazaki, 2009. Improved Evolving Kernel of Fisher’s Discriminant Analysis for Classification Problem. Journal of Applied Sciences, 9: 2313-2318.

DOI: 10.3923/jas.2009.2313.2318

URL: https://scialert.net/abstract/?doi=jas.2009.2313.2318

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