Abstract
We present a parametric extension of the Bayesian Rough Set (BRS) model. Its properties are investigated in relation to non-parametric BRS, classical Rough Set (RS) model and the Variable Precision Rough Set (VPRS) model.
Supported by the research grant of the Research Centre of PJIIT, as well as the research grant of the Natural Sciences and Engineering Research Council of Canada.
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Ślęzak, D., Ziarko, W. (2003). Variable Precision Bayesian Rough Set Model. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_46
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DOI: https://doi.org/10.1007/3-540-39205-X_46
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