Authors: Yuhua Qian, Hu Zhang, Yanli Sang, Jiye Liang

Abstract:

The Bayesian decision-theoretic rough sets propose a framework for studying rough set approximations using probabilistic theory, which can interprete the parameters from existing forms of probabilistic approaches to rough sets. Exploring rough sets in the viewpoint of multigranulation is becoming one of desirable directions in rough set theory, in which lower/upper approximations are approximated by granular structures induced by multiple binary relations. Through combining these two ideas, the objective of this study is to develop a new multigranulation rough set model, called a multigranulation decision-theoretic rough set. Many existing multigranulation rough set models can be derived from the multigranulation decision-theoretic rough set framework.

Keywords： Decision-theoretic rough sets, Granular computing, Multigranulation, Bayesian decision theory

Multigranulation decision-theoretic rough sets.pdf

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Tue Jun 17 09:45:00 CST 2014