Discovering surprising patterns by detecting occurrences of Simpson's paradox

Fabris, Carem C. and Freitas, Alex A. (2000) Discovering surprising patterns by detecting occurrences of Simpson's paradox. In: 19th SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence (ES99), Dec 13-15, 1999, Cambridge, England. (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)

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This paper addresses the discovery of surprising patterns. Recently, several authors have addressed the task of discovering surprising prediction rules. However, we do not focus on prediction rules, but rather on a quite different kind of pattern, namely the occurrence of Simpson's paradox. Intuitively, the fact that this is a paradox suggests that it has a great potential to be a surprising pattern for the user. With this motivation, we make the detection of Simpson's paradox the central goal of a data mining algorithm explicitly designed to discover surprising patterns. We present computational results showing surprising occurrences of the paradox in some public-domain data sets. In addition, we propose a method for ranking the discovered instances of the paradox in decreasing order of estimated degree of surprisingness.

Item Type: Conference or workshop item (Paper)
Additional information: Proceedings 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: 02 Sep 2009 15:44
Last Modified: 18 Jun 2014 09:00
Resource URI: (The current URI for this page, for reference purposes)
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