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.
|Title of host publication||Rough sets and knowledge technology: proceedings of the 7th international conference|
|Editors||T. Li, H. Nguyen, G. Wang, J. Grzymala-Busse, R. Janicki, A. Hassanien, H. Yu|
|Place of Publication||Berlin|
|Number of pages||8|
|Publication status||Published - 2012|
|Name||Lecture notes in computer science|