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Hybrid Pattern Recognition Using a Combination of Different Features

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2015, 20(11), pp.9-16
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Sang-Il Choi 1

1단국대학교

Accredited

ABSTRACT

We propose a hybrid pattern recognition method that effectively combines two different features for improving data classification. We first extract the PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) features, both of which are widely used in pattern recognition, to construct a set of basic features, and then evaluate the separability of each basic feature. According to the results of evaluation, we select only the basic features that contain a large amount of discriminative information for construction of the combined features. The experimental results for the various data sets in the UCI machine learning repository show that using the proposed combined features give better recognition rates than when solely using the PCA or LDA features

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.