A Multi-criteria approach for the evaluation of rule interestingness

Freitas, A.A. (1998) A Multi-criteria approach for the evaluation of rule interestingness. In: Data Mining (Proc Int Conf Rio de Janeiro, Brazil), Sep 02-04, 1998, Rio Janeiro, Brazil,. (The full text of this publication is not available from this repository)

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Abstract

This paper studies several criteria for evaluating rule interestingness. It first reviews some rule interestingness principles with respect to the widely-used criteria of coverage, completeness and confidence factor of a rule. It then considers several additional factors (or criteria) influencing rule interestingness that have been somewhat neglected in the literature on rule interestingness. As a result, this paper argues that rule interestingness measures should be extended to take into account the additional rule-quality factors of disjunct size, imbalance of the class distribution, attribute interestingness, misclassification costs and the asymmetry of classification rules. The paper also presents a case study on how a popular rule interestingness measure can be extended to take into account the proposed additional rule-quality factors.

Item Type: Conference or workshop item (Paper)
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 25 Aug 2009 16:29
Last Modified: 08 Jun 2012 13:24
Resource URI: http://kar.kent.ac.uk/id/eprint/21601 (The current URI for this page, for reference purposes)
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