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- W2091298464 abstract "The article presents a parametric Bayesian extension of the rough set model, where the set approximations are defined by using the prior probability as a reference. It is shown that the quality of the Bayesian rough set models can be evaluated using probabilistic gain function which is suitable for easy computation of attribute reducts. It leads to the Bayesian style criteria for the attribute reduction within the rough set framework." @default.
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- W2091298464 date "2003-03-01" @default.
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- W2091298464 title "Attribute Reduction in the Bayesian Version of Variable Precision Rough Set Model" @default.
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- W2091298464 doi "https://doi.org/10.1016/s1571-0661(04)80724-2" @default.
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