An efficient rough set model called double-local rough sets is proposed. The proposed model can process both completely labeled data and partially labeled data. The proposed method is an enhancement version of local rough sets in computational performance.
We propose an enhanced local rough set framework called double-local rough sets, by introducing the notion of local equivalence classes.
An efficient rough set model called double-local rough sets is proposed. · The proposed model can process both completely labeled data and partially labeled data ...
To overcome this limitation, we propose an enhanced local rough set framework called double-local rough sets, by introducing the notion of local equivalence ...
Double-local rough sets for efficient data mining ; Journal: Information Sciences, 2021, p. 475-498 ; Publisher: Elsevier BV ; Authors: Guoqiang Wang, Tianrui Li, ...
Feb 16, 2023 · In order to improve the computing efficiency of three approximation regions of probabilistic rough sets, we propose a double-local conditional ...
Experimental analysis. In this experimental analysis, we want to verify the advantages of the LARC algorithm from two sides: over-fitting and efficiency.
Efficient and robust heuristics exist for reduct construction task. Searching for reducts may be done efficiently with the use of evolutionary computation.
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Apr 1, 2024 · This research aims to contribute to the analysis of hybrid data processing models based on neighborhood rough sets by investigating the inherent relationships ...