On Information-Theoretic Measures of Attribute Importance

  • Authors:
  • Y. Y. Yao;S. K. Michael Wong;Cory J. Butz

  • Affiliations:
  • -;-;-

  • Venue:
  • PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
  • Year:
  • 1999

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Abstract

An attribute is deemed important in data mining if it partitions the database such that previously unknown regularities are observable. Many information-theoretic measures have been applied to quantify the importance of an attribute. In this paper, we summarize and critically analyze these measures.