EFFECTS OF USING REDUCTS IN THE PERFORMANCE OF THE IRBASIR ALGORITHM

Feature selection is a preprocessing technique with the objective of finding a subset of attributes that improve the classifier performance. In this paper, a new algorithm (IRBASIRRED) is presented for the generation of learning rules that uses feature selection to obtain the knowledge model. Also a new method (REDUCTSIM) is presented for the reduct's calculation using the optimization technique, Particle Swarm Optimization (PSO). The proposed algorithm was tested on data sets from the UCI Repository and compared with the algorithms: C4.5, LEM2, MODLEM, EXPLORE and IRBASIR. The results obtained showed that IRBASIRRED is a method that generates classification rules using subsets of attributes, obtaining better results than the algorithm where all attributes are used.

Bibliographic Details

Main Authors:	FERNÁNDEZ,YUMILKA B., BELLO,RAFAEL, FILIBERTO,YAIMA, FRIAS,MABEL, CABALLERO,YAILE
Format:	Digital revista
Language:	English
Published:	Universidad Nacional de Colombia 2013
Online Access:	http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532013000600022
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