Title :
A Rough Set Based Hybrid Method to Feature Selection
Author_Institution :
Coll. of Comput. Sci., Beijing Univ. of Technol., Beijing
Abstract :
Features selection is a process to find the optimal subset of features that satisfy certain criteria. The aim of feature selection is to remove unnecessary features to the target concept. This paper investigates some basic concepts of rough set theory and ant colony optimization. Based on these studies, a hybrid approach to feature selection on combination of ant colony optimization and rough set theory is proposed. Experimental results obtained show this hybrid approach is a promising method for feature selection.
Keywords :
feature extraction; optimisation; rough set theory; ant colony optimization; feature selection; rough set based hybrid method; Ant colony optimization; Computational modeling; Computer science; Educational institutions; Helium; Information systems; Knowledge acquisition; Machine learning; Optimization methods; Set theory;
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
DOI :
10.1109/KAM.2008.12
