On the feature selection criterion based on an approximation of multidimensional mutual information

Kiran S. Balagani, Vir V. Phoha

Research output: Contribution to journalReview article

34 Scopus citations

Abstract

We derive the feature selection criterion presented in [1] and [2] from the multidimensional mutual information between features and the class. Our derivation: 1) specifies and validates the lower-order dependency assumptions of the criterion and 2) mathematically justifies the utility of the criterion by relating it to Bayes classification error.

Original languageEnglish (US)
Article number5432207
Pages (from-to)1342-1343
Number of pages2
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume32
Issue number7
DOIs
StatePublished - May 28 2010
Externally publishedYes

Keywords

  • Bayes classification error
  • Entropy
  • Entropy estimation
  • Feature selection
  • Mutual information

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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