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Standardizing interestingness measures for association rules
Date Issued
2018-12
Date Available
2019-05-20T13:13:25Z
Abstract
Interestingness measures provide information about association rules. The value of an interestingness measure is often interpreted relative to the overall range of the interestingness measure. However, properties of individual association rules can further restrict what value an interestingness measure can achieve. These additional constraints are not typically taken into account in analysis, potentially misleading the investigator. Considering the value of an interestingness measure relative to this further constrained range provides greater insight than the original range alone and can even alter researchers' impressions of the data. Standardizing interestingness measures takes these additional restrictions into account, resulting in values that provide a relative measure of the attainable values. We explore the impacts of standardizing interestingness measures on real and simulated data.
Other Sponsorship
Insight Research Centre
Natural Sciences and Engineering Research Council of Canada
Ontario Ministry of Research and Innovation
Type of Material
Journal Article
Publisher
Wiley
Journal
Statistical Analysis and Data Mining
Volume
11
Issue
6
Start Page
282
End Page
295
Copyright (Published Version)
2018 Wiley
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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Owning collection
Scopus© citations
13
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