Discovering Surprising Patterns by Detecting Occurrences of Simpson’s Paradox
作者： Carem C. Fabris , Alex A. Freitas
DOI: 10.1007/978-1-4471-0745-3_10
关键词:
摘要: This paper addresses the discovery of surprising patterns. Recently, several authors have addressed task discovering prediction rules. However, we do not focus on rules, but rather a quite different kind pattern, namely occurrence Simpson’s paradox. Intuitively, fact that this is paradox suggests it has great potential to be pattern for user. With motivation, make detection central goal data mining algorithm explicitly designed discover We present computational results showing occurrences in some public-domain sets. In addition, propose method ranking discovered instances decreasing order estimated degree surprisingness.
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