Title of article :
Wrapper Feature Selection using Discrete Cuckoo Optimization Algorithm
Author/Authors :
Mousavirad ، S.J. نويسنده Department of Computer and Electrical Engineering, University of Kashan, Kashan, Iran Mousavirad , S.J. , Ebrahimpour-Komleh، H. نويسنده Department of Computer and Electrical Engineering, University of Kashan, Kashan, Iran Ebrahimpour-Komleh, H.
Issue Information :
فصلنامه با شماره پیاپی 0 سال 2014
Abstract :
Feature subset selection plays an important role in data mining. The aim of feature selection is to remove redundant and irrelevant features without reducing the accuracy. Cuckoo optimization algorithm (COA) is a new population based algorithm which is inspired by the lifestyle of a species of bird called cuckoo. In this paper, we introduce a new approach based on COA for feature subset selection. To verify the efficiency of our algorithm, experiments carried out on some datasets. The results demonstrate that proposed algorithm can provide an optimal solution for feature subset selection problem.
Journal title :
International Journal of Mechatronics, Electrical and Computer Technology (IJMEC)
Journal title :
International Journal of Mechatronics, Electrical and Computer Technology (IJMEC)