Title :
The Overview of Feature Selection Algorithms Based Swarm Intelligence and Rough Set
Author :
Chengmin, Sun ; Dayou, Liu
Author_Institution :
Dept. of Comput. Sci., Jilin Univ., Changchun, China
Abstract :
Compared with traditional algorithms of rough set feature selection, the stochastic algorithms for feature selection based on rough set and swarm intelligence are popular. This paper gives the overview of rough set algorithms for feature selection based on ant colony optimization, and algorithms based on particle swarm optimization.
Keywords :
data mining; particle swarm optimisation; rough set theory; stochastic processes; ant colony optimization; data mining; feature selection algorithms; particle swarm optimization; rough set; stochastic algorithms; swarm intelligence; Algorithm design and analysis; Ant colony optimization; Classification algorithms; Educational institutions; Particle swarm optimization; Pattern recognition; Set theory; Ant Colony Optimization; Feature Selection; Particle Swarm Opitimation; Rough Set; Swarm Intelligence;
Conference_Titel :
Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
Conference_Location :
Hainan
Print_ISBN :
978-1-4577-2008-6
DOI :
10.1109/CIS.2011.42
