A Multi-granularity Rough Set Algorithm for Attribute Reduction through Particles Particle Swarm Optimization

Citation:
Guangyao Dai, H. L.  Zongmei Wang, Chao Yang, Aboul Ella Hassanieny, and W. Yang, "A Multi-granularity Rough Set Algorithm for Attribute Reduction through Particles Particle Swarm Optimization", IEEE iInternational Computer Engineering Conference - ICENCO , Cairo, 30 Dec, 2015.

Date Presented:

30 Dec

Abstract—Multi-granularity analysis is an important manifestation
of human cognitive ability which can obtain more
reasonable and satisfactory solutions from multiple perspectives
and multiple levels. In this paper, we present a multiknowledge
rapid reduction strategy combined with particle
swarm algorithm based on optimistic multi-granularity rough
sets. We evaluated the performance of our approach using the
Statlog (Heart) Data Set and the corresponding computational
experiments were completed. The empirical results indicate
that our approach is effective at identifying multiple factors
and usually produces multiple candidate reducts.