Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Feature Impact Evaluation Based Pattern Classification System

  • Rhee, Hyun-Sook (Dept. of Software Engineering, Dongyang Mirae University)
  • Received : 2018.09.12
  • Accepted : 2018.11.07
  • Published : 2018.11.30
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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.

Keywords

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Fig. 1. Feature Impact Evaluation Based Pattern Classification Model

Table 1. Feature information

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Table 2. Features Rank Based on Feature Impact Evaluation

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Table 3. Comparison of Classification Accuracy

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