Interestingness Measures for Fixed Consequent Rules

Hills, Jon, Davis, Luke M. and Bagnall, Anthony (2012) Interestingness Measures for Fixed Consequent Rules. Lecture Notes in Computer Sciences, 7435. pp. 68-75. ISSN 0302-9743

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Abstract

Many different rule interestingness measures have been proposed in the literature; we show that, under two assumptions, at least twelve of these measures are proportional to Confidence. We consider rules with a fixed consequent, generated from a fixed data set. From these assumptions, we prove that Satisfaction, Ohsaki’s Conviction, Added Value, Brin’s Interest/Lift/Strength, Brin’s Conviction, Certainty Factor/Loevinger, Mutual Information, Interestingness, Sebag-Schonauer, Ganascia Index, Odd Multiplier, and Example/counter-example Rate are all monotonic with respect to Confidence. Hence, for ordering sets of partial classification rules with a fixed consequent, the Confidence measure is equivalent to any of the twelve other measures.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and Statistics
Depositing User:	Users 2731 not found.
Date Deposited:	12 Sep 2012 11:42
Last Modified:	09 Nov 2022 11:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/39534
DOI:	10.1007/978-3-642-32639-4_9

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