Resumen

FERNANDEZ, YUMILKA B. et al. EFFECTS OF USING REDUCTS IN THE PERFORMANCE OF THE IRBASIR ALGORITHM. Dyna rev.fac.nac.minas [online]. 2013, vol.80, n.182, pp.182-190. ISSN 0012-7353.

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.

Palabras clave : Feature selection; classification rules; Particle Swarm Optimization.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )