Paper Info
Title
Implementation and integration of algorithms into the KEEL data-mining software tool
Abstract
This work is related to the KEEL (Knowledge Extraction based on Evolutionary Learning) tool, a non-commercial software that supports data management, design of experiments and an educational section. The KEEL software tool is devoted to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering, pattern mining and so on. These features implies an advantage for the research and educational field. The aim of this contribution is to present some guidelines for including new algorithms in KEEL, helping the researchers to make their methods easily accessible for other authors and to compare the results of many approaches already included within the KEEL software. By providing a source code template, the developer does not need to take into account the basic requirements of the KEEL software tool, and he or she has only to focus in the designing and encoding of his or hers approach.
Year
DOI
Venue
2009
10.1007/978-3-642-04394-9_68
IDEAL
Keywords
Field
DocType
keel software,keel data-mining software tool,keel software tool,basic requirement,knowledge extraction,educational section,non-commercial software,data mining problem,educational field,data management,evolutionary learning,design of experiment,source code,machine learning,evolutionary algorithm,data mining
Data mining,Keel,Evolutionary algorithm,Source code,Computer science,Software,Artificial intelligence,Cluster analysis,Algorithm,Knowledge extraction,Data management,Machine learning,Encoding (memory)
Conference
Volume
ISSN
ISBN
5788
0302-9743
3-642-04393-3
Citations 
PageRank 
References 
5
0.49
9
Authors
5
Name
Order
Citations
PageRank
Alberto Fernández1173444.38
Julian Luengo2241877.15
Joaquín Derrac3255264.42
J. Alcalá-Fdez4205974.03
Francisco Herrera5273911168.49