Fuzzy classification using self-organizing map and learning vector quantization

  • Authors:

  • Ning Chen

  • Affiliations:

  • Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Portugal

  • Venue:
  • CASDMKM'04 Proceedings of the 2004 Chinese academy of sciences conference on Data Mining and Knowledge Management
  • Year:
  • 2004

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Abstract

Fuzzy classification proposes an approach to solve uncertainty problem in classification tasks. It assigns an instance to more than one class with different degrees instead of a definite class by crisp classification. This paper studies the usage of fuzzy strategy in classification. Two fuzzy algorithms for sequential self-organizing map and learning vector quantization are proposed based on fuzzy projection and learning rules. The derived classifiers are able to provide fuzzy classes when classifying new data. Experiments show the effectiveness of proposed algorithms in terms of classification accuracy.