Theoretical Comparison of a Class of Feature Selection Criteria in Pattern Recognition

  • Authors:

  • C. H. Chen

  • Affiliations:

  • -

  • Venue:
  • IEEE Transactions on Computers
  • Year:
  • 1971

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Abstract

The distance measures and the information functions for feature selection are compared. The comparison is based on the available tight upper and lower bounds of the probability of misrecognition, the rates of change of such probability, the effectiveness of a feature subset, and the computational complexity.