Abstract
Analysis of rule interestingness measures with respect to their properties is an important research area helping to identify groups of measures that are truly meaningful. In this article, we analyze property Ex 1, of preservation of extremes, in a group of confirmation measures. We consider normalization as a mean to transform them so that they would obtain property Ex 1 and we introduce three alternative approaches to the problem: an approach inspired by Nicod, Bayesian, and likelihoodist approach. We analyze the results of the normalizations of seven measures with respect to property Ex 1 and show which approaches lead to the desirable results. Moreover, we extend the group of ordinally non-equivalent measures possessing valuable property Ex 1.
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Greco, S., Słowiński, R., Szczȩch, I. (2010). Alternative Normalization Schemas for Bayesian Confirmation Measures. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Computational Intelligence for Knowledge-Based Systems Design. IPMU 2010. Lecture Notes in Computer Science(), vol 6178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14049-5_24
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DOI: https://doi.org/10.1007/978-3-642-14049-5_24
Publisher Name: Springer, Berlin, Heidelberg
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