Attribute Reduction Algorithm Based on Power Graph

Bo-chen KOU, Li-wei TANG

Abstract


At present, the attribute reduction based on granular computing is mostly based on rough set theory, and the attribute reduction based on granular computing is studied now. The problem of attribute reduction is transformed into the problem of searching in the granular-power graph, and a continuous value attribute reduction algorithm based on granular-power graph combined with fuzzy relation is proposed. The results of simulation show that the algorithm can reduce the value of continuous attributes, which can enhance the practicality of top-down attribute reduction

Keywords


Granular computing, Attribute reduction, Granular-power graph


DOI
10.12783/dtetr/icmca2017/12357

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