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Analysis of symmetry properties for bayesian confirmation measures

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

The paper considers symmetry properties of Bayesian confirmation measures, which constitute an important group of interestingness measures for evaluation of rules induced from data. We demonstrate that the symmetry properties proposed in the literature do not fully reflect the concept of confirmation. We conduct a thorough analysis of the symmetries regarding that the confirmation should express how much more probable the rule’s hypothesis is when the premise is present rather than when the premise is absent. As a result we point out which symmetries are desired for Bayesian confirmation measures and which are truly unattractive. Such knowledge is a valuable tools for assessing the quality and usefulness of measures.
Original languageEnglish
Title of host publicationRough sets and knowledge technology: proceedings of the 7th international conference
EditorsT. Li, H. Nguyen, G. Wang, J. Grzymala-Busse, R. Janicki, A. Hassanien, H. Yu
Place of PublicationBerlin
PublisherSpringer
Pages207-214
Number of pages8
Volume7414
Edition7414
ISBN (Print)9783642318993
DOIs
Publication statusPublished - 2012

Publication series

NameLecture notes in computer science
PublisherSpringer
Number7414
ISSN (Print)0302-9743

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