A Probabilistic Framework Towards the Parameterization of Association Rule Interestingness Measures

Stéphane Lallich (), Benoît Vaillant () and Philippe Lenca ()
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Stéphane Lallich: Université Lyon 2
Benoît Vaillant: GET–ENST Bretagne–Département LUSSI, CNRS UMR 2872 TAMCIC
Philippe Lenca: GET–ENST Bretagne–Département LUSSI, CNRS UMR 2872 TAMCIC

Methodology and Computing in Applied Probability, 2007, vol. 9, issue 3, 447-463

Abstract: Abstract In this paper, we first present an original and synthetic overview of the most commonly used association rule interestingness measures. These measures usually relate the confidence of a rule to an independence reference situation. Yet, some relate it to indetermination, or impose a minimum confidence threshold. We propose a systematic generalization of these measures, taking into account a reference point chosen by an expert in order to appreciate the confidence of a rule. This generalization introduces new connections between measures, and leads to the enhancement of some of them. Finally we propose new parameterized possibilities.

Keywords: Interestingness measure; Association rule; Independence; Indetermination; Probabilistic models; 62H15; 62H17; 62H20; 68T10 (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11009-007-9025-7

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