Modifications to Bayesian Rough Set Model and Rough Vague Sets

Keqiu Li, Deqin Yan, W. Qu
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引用次数: 4

Abstract

The variable precision rough set (VPRS) model generalizes the Pawlak rough set model with variable parameters. The Bayesian rough set (BRS) model improves the VPRS model with non-parametric modification by using the prior probability as a reference. This paper presents two research results related to rough set model and rough vague sets. One is a modification to the Bayesian rough set model and the other is a modification to rough vague sets. First, the Bayesian rough set model is analyzed and discussed. Second, a modification to this model is proposed and verified. Finally, a modification to rough vague sets is presented and its related properties are discussed..
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对贝叶斯粗糙集模型和粗糙模糊集的修正
变精度粗糙集(VPRS)模型是对变参数Pawlak粗糙集模型的推广。贝叶斯粗糙集(BRS)模型以先验概率为参考,对VPRS模型进行非参数修正。本文介绍了粗糙集模型和粗糙模糊集两方面的研究成果。一种是对贝叶斯粗糙集模型的改进,另一种是对粗糙模糊集的改进。首先,对贝叶斯粗糙集模型进行了分析和讨论。其次,对该模型进行了修正并进行了验证。最后给出了粗糙模糊集的一种修正,并讨论了其相关性质。
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