Abstract
Bayesian confirmation theory considers a variety of non-equivalent confirmation measures quantifying the degree to which a piece of evidence supports a hypothesis. In this paper, we apply some of the most relevant confirmation measures within the rough set approach. Moreover, we discuss interesting properties of these confirmation measures and we propose a new property of monotonicity that is particularly relevant within rough set approach. The main result of this paper states which one of the confirmation measures considered in the literature have the desirable properties from the viewpoint of the rough set approach.
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Greco, S., Pawlak, Z., Słowiński, R. (2004). Bayesian Confirmation Measures within Rough Set Approach. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_31
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DOI: https://doi.org/10.1007/978-3-540-25929-9_31
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Print ISBN: 978-3-540-22117-3
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