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11

PAKDD
1999
ACM

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On Information-Theoretic Measures of Attribute Importance

13 years 9 months ago

On Information-Theoretic Measures of Attribute Importance

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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.

Yiyu Yao, S. K. Michael Wong, Cory J. Butz

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Data Mining | Many Information-theoretic Measures | PAKDD 1999 | Unknown Regularities |

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Added	04 Aug 2010
Updated	04 Aug 2010
Type	Conference
Year	1999
Where	PAKDD
Authors	Yiyu Yao, S. K. Michael Wong, Cory J. Butz

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