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In this paper, we propose a way to reduce the attributes of covering decision systems, which are databases characterized by covers.
Here, we solve this problem in inconsistent covering decision systems.
First, we define consistent and inconsistent covering decision systems and their attribute reductions.
However, the existing related family-based methods have to recompute reducts for dynamic covering decision information systems.
Secondly, in inconsistent covering decision systems, the limitary conditional entropy of the covering is proposed and attribute reductions are defined.
In this paper, we propose some new approaches for attribute reduction in covering decision systems from the viewpoint of information theory.
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