Knowledge reduction of dynamic covering decision information systems with varying attribute values
April 12, 2015 Β· Declared Dead Β· π International Journal of Machine Learning and Cybernetics
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Authors
Mingjie Cai
arXiv ID
1504.02930
Category
cs.IT: Information Theory
Cross-listed
cs.AI
Citations
22
Venue
International Journal of Machine Learning and Cybernetics
Last Checked
4 months ago
Abstract
Knowledge reduction of dynamic covering information systems involves with the time in practical situations. In this paper, we provide incremental approaches to computing the type-1 and type-2 characteristic matrices of dynamic coverings because of varying attribute values. Then we present incremental algorithms of constructing the second and sixth approximations of sets by using characteristic matrices. We employ experimental results to illustrate that the incremental approaches are effective to calculate approximations of sets in dynamic covering information systems. Finally, we perform knowledge reduction of dynamic covering information systems with the incremental approaches.
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