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Feature Impact Evaluation Based Pattern Classification System

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2018, 23(11), pp.25-30
  • DOI : 10.9708/jksci.2018.23.11.025
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : September 12, 2018
  • Accepted : November 7, 2018
  • Published : November 30, 2018

Hyun-Sook Rhee 1

1동양미래대학교

Accredited

ABSTRACT

Pattern classification system is often an important component of intelligent systems. In this paper, we present a pattern classification system consisted of the feature selection module, knowledge base construction module and decision module. We introduce a feature impact evaluation selection method based on fuzzy cluster analysis considering computational approach and generalization capability of given data characteristics. A fuzzy neural network, OFUN-NET based on unsupervised learning data mining technique produces knowledge base for representative clusters. 240 blemish pattern images are prepared and applied to the proposed system. Experimental results show the feasibility of the proposed classification system as an automating defect inspection tool.

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