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Proposal of Weight Adjustment Methods Using Statistical Information in Fuzzy Weighted Mean Classifiers

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2009, 14(7), pp.9-15
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Woo, Young Woon 1 Kwang Baek Kim ORD ID 2 허경용 3

1동의대학교
2신라대학교
3University of Florida

Accredited

ABSTRACT

The fuzzy weighted mean classifier is one of the most common classification models and could achieve high performance by adjusting the weights. However, the weights were generally decided based on the experience of experts, which made the resulting classifiers to suffer the lack of consistency and objectivity. To resolve this problem, in this paper, a weight deciding method based on the statistics of the data is introduced, which ensures the learned classifiers to be consistent and objective. To investigate the effectiveness of the proposed methods, Iris data set available from UCI machine learning repository is used and promising results are obtained.

Citation status

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