#5763. Random sampling accelerator for attribute reduction

July 2026publication date
Proposal available till 11-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Applied Mathematics;
Theoretical Computer Science;
Software;
Artificial Intelligence;
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Abstract:
As one of the crucial topics in the development of rough set, attribute reduction has received extensive attentions because it is practical and interpretable for us to perform dimensional reduction or feature selection. Currently, to further improve the efficiency of searching reducts, many researchers have devoted themselves to designing various accelerative mechanisms. Among these existing results, it should be pointed out that the accelerators designed by reducing the scale of samples strongly depend on the distribution of data. To fill such a gap, an accelerator based on the random sampling is developed.
Keywords:
Accelerator; Attribute reduction; Random sampling; Rough set

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