On Information-Theoretic Measures of Attribute Importance

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.

• Type: Conference
• Year: 1999
• Where: PAKDD
• Authors: Yiyu Yao, S. K. Michael Wong, Cory J. Butz
• Keywords: Data Mining, Many Information-theoretic Measures, PAKDD 1999, Unknown Regularities