A model based on ant colony system and rough set theory to feature selection

Authors:

R. Bello
R. Bello
Y. Caballero
Y. Caballero
P. Vrancx
P. Vrancx

Open Access

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25 June 2005

conference paper
Published by Association for Computing Machinery (ACM)

p. 275-276
DOI:10.1145/1068009.1068053

Abstract

In this paper we propose a hybrid approach to feature selection based on Ant Colony System algorithm and Rough Set Theory. Rough Set Theory offers the heuristic function to measure the quality of a single subset. We have studied the influence of the setting of the parameters for this problem, in particular for finding reducts. Experimental results show this hybrid approach is a promising method for features selection.

Keywords

ACO META-HEURISTIC
FEATURE SELECTION
REDUCTS
ROUGH SET THEORY

This publication has 3 references indexed in Scilit:

Ant Colony Optimization
2004
The Equation for Response to Selection and Its Use for Prediction
Evolutionary Computation, 1997
Rough sets
International Journal of Parallel Programming, 1982