Fuzzy-Rough MRMS Method for Relevant and Significant Attribute Selection

  title={Fuzzy-Rough MRMS Method for Relevant and Significant Attribute Selection},
  author={Pradipta Maji and Partha Garai},
Feature selection refers to the problem of selecting the input attributes or features that are most effective to predict the sample categories. In this regard, a feature selection method is presented based on fuzzy-rough sets by maximizing both relevance and significance of the selected features. The paper also presents different feature evaluation criteria such as dependency, relevance, redundancy and significance for attribute selection task using fuzzy-rough sets. The performance of… CONTINUE READING
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Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing

  • S. K. Pal, S. Mitra
  • John Wiley & Sons, New York
  • 1999
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