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A Multi-criteria approach for the evaluation of rule interestingness

Freitas, Alex A. (1998) A Multi-criteria approach for the evaluation of rule interestingness. In: Ebecken, Nelson, ed. Data Mining. WIT Press, pp. 7-20. ISBN 978-1-85312-677-2. (doi:10.2495/DATA980021) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:21601)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
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http://dx.doi.org/10.2495/DATA980021

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: Book section
DOI/Identification number: 10.2495/DATA980021
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 25 Aug 2009 16:29 UTC
Last Modified: 16 Feb 2021 12:32 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21601 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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