@misc{10481/77963,
year = {2014},
month = {12},
url = {https://hdl.handle.net/10481/77963},
abstract = {Inductive learning has been—and still is—one of the most important methods that can be applied in
classification problems. Knowledge is usually represented using rules that establish relationships between
the problem variables. SLAVE (Structural Learning Algorithm in a Vague Environment) was one of the
first fuzzy-rule learning algorithms, and since its first implementation in 1994 it has been frequently
used to benchmark new algorithms. Over time, the algorithm has undergone several modifications, and
identifying the different versions developed is not an easy task. In this work we present a study of the
evolution of the SLAVE algorithm from 1996 to date, marking the most important landmarks as definitive
versions. In order to add these final versions to the KEEL platform, Java implementations have been
developed. Finally, we describe the parameters used and the results obtained in the experimental study.},
organization = {Andalusian Regional Government project	P09-TIC-04813},
organization = {Spanish Government	TIN2012-38969},
organization = {European Commission},
publisher = {Atlantis},
keywords = {Classification problems},
keywords = {Feature selection},
keywords = {Fuzzy Rules},
keywords = {Genetic algorithms},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {Overview of the SLAVE learning algorithm: A review of its evolution and prospects},
doi = {10.1080/18756891.2014.967008},
author = {García, David and González Muñoz, Antonio and Pérez Rodríguez, Francisco G.Raúl},
}