KEEL: a software tool to assess evolutionary algorithms for data mining problems

被引：1175

作者：

Alcala-Fdez, J. ^{[1
]}

Sanchez, L. ^{[2
]}

Garcia, S. ^{[1
]}

del Jesus, M. J. ^{[3
]}

Ventura, S. ^{[4
]}

Garrell, J. M. ^{[5
]}

Otero, J. ^{[2
]}

Romero, C. ^{[4
]}

Bacardit, J. ^{[6
]}

Rivas, V. M. ^{[3
]}

Fernandez, J. C. ^{[4
]}

Herrera, F. ^{[1
]}

机构：

[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, E-18071 Granada, Spain

[2] Univ Oviedo, Dept Comp Sci, Gijon 33204, Spain

[3] Univ Jaen, Dept Comp Sci, Jaen 23071, Spain

[4] Univ Cordoba, Dept Numer Anal & Comp Sci, E-14071 Cordoba, Spain

[5] Univ Ramon Llull, Dept Comp Sci, Barcelona 08022, Spain

[6] Univ Nottingham, Dept Comp Sci & Informat Technol, Nottingham NG8 1BB, England

来源：

SOFT COMPUTING | 2009年 / 13卷 / 03期

基金：

英国工程与自然科学研究理事会;

关键词：

Computer-based education; Data mining; Evolutionary computation; Experimental design; Graphical programming; !text type='Java']Java[!/text; Knowledge extraction; Machine learning; METHODOLOGY; CLASSIFIERS; REDUCTION; INDUCTION; FRAMEWORK;

D O I：

10.1007/s00500-008-0323-y

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a software tool named KEEL which is a software tool to assess evolutionary algorithms for Data Mining problems of various kinds including as regression, classification, unsupervised learning, etc. It includes evolutionary learning algorithms based on different approaches: Pittsburgh, Michigan and IRL, as well as the integration of evolutionary learning techniques with different pre-processing techniques, allowing it to perform a complete analysis of any learning model in comparison to existing software tools. Moreover, KEEL has been designed with a double goal: research and educational.

引用

页码：307 / 318

页数：12

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