A rough set-based incremental approach for learning knowledge in dynamic incomplete information systems
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Publication:459049
DOI10.1016/j.ijar.2014.05.009zbMath1433.68449OpenAlexW2094774132MaRDI QIDQ459049
Junbo Zhang, Dun Liu, Tianrui Li
Publication date: 8 October 2014
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ijar.2014.05.009
Related Items (14)
Cost-sensitive sequential three-way decision modeling using a deep neural network ⋮ A three-way decisions model with probabilistic rough sets for stream computing ⋮ General expression of knowledge granularity based on a fuzzy relation matrix ⋮ Matrix-based approaches for updating three-way regions in incomplete information systems with the variation of attributes ⋮ Efficient approaches for maintaining dominance-based multigranulation approximations with incremental granular structures ⋮ Possibility measure based fuzzy support function machine for set-based fuzzy classifications ⋮ Attribute Reduction of Incomplete Information Systems: An Intuitionistic Fuzzy Rough Set Approach ⋮ A Further Investigation to Relative Reducts of Decision Information Systems ⋮ Dominance-based rough set approach to incomplete ordered information systems ⋮ Knowledge reduction of dynamic covering decision information systems when varying covering cardinalities ⋮ Fuzzy set-valued information systems and the algorithm of filling missing values for incomplete information systems ⋮ Incremental three-way neighborhood approach for dynamic incomplete hybrid data ⋮ Incremental updating probabilistic neighborhood three-way regions with time-evolving attributes ⋮ Matrix-based set approximations and reductions in covering decision information systems
Uses Software
Cites Work
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