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

J. Alcalá-Fdez; Luciano Sánchez; Salva García; M. J. del Jesus; S. Ventura; Josep M. Garrell; J. Otero; C. Romero; J. Bacardit; V. M. Rivas; J. C. Fernández; F. Herrera

doi:10.1007/s00500-008-0323-y

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

J. Alcalá-Fdez^*
, Luciano Sánchez
, Salva García
, M. J. del Jesus
, S. Ventura
, Josep M. Garrell
, J. Otero
, C. Romero
, J. Bacardit
, V. M. Rivas
, J. C. Fernández
, F. Herrera

^*Corresponding author for this work

Research output: Indexed journal article › Article › peer-review

1412 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	307-318
Number of pages	12
Journal	Soft Computing
Volume	13
Issue number	3
DOIs	https://doi.org/10.1007/s00500-008-0323-y
Publication status	Published - 2009

Keywords

Computer-based education
Data mining
Evolutionary computation
Experimental design
Graphical programming
Java
Knowledge extraction
Machine learning

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10.1007/s00500-008-0323-y

Cite this

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title = "KEEL: A software tool to assess evolutionary algorithms for data mining problems",

abstract = "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.",

keywords = "Computer-based education, Data mining, Evolutionary computation, Experimental design, Graphical programming, Java, Knowledge extraction, Machine learning",

author = "J. Alcal{\'a}-Fdez and Luciano S{\'a}nchez and Salva Garc{\'i}a and \{del Jesus\}, \{M. J.\} and S. Ventura and Garrell, \{Josep M.\} and J. Otero and C. Romero and J. Bacardit and Rivas, \{V. M.\} and Fern{\'a}ndez, \{J. C.\} and F. Herrera",

year = "2009",

doi = "10.1007/s00500-008-0323-y",

language = "English",

volume = "13",

pages = "307--318",

journal = "Soft Computing",

issn = "1432-7643",

publisher = "Springer Science and Business Media Deutschland GmbH",

number = "3",

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TY - JOUR

T1 - KEEL

T2 - A software tool to assess evolutionary algorithms for data mining problems

AU - Alcalá-Fdez, J.

AU - Sánchez, Luciano

AU - García, Salva

AU - del Jesus, M. J.

AU - Ventura, S.

AU - Garrell, Josep M.

AU - Otero, J.

AU - Romero, C.

AU - Bacardit, J.

AU - Rivas, V. M.

AU - Fernández, J. C.

AU - Herrera, F.

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Computer-based education

KW - Data mining

KW - Evolutionary computation

KW - Experimental design

KW - Graphical programming

KW - Java

KW - Knowledge extraction

KW - Machine learning

UR - https://www.scopus.com/pages/publications/55549103698

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DO - 10.1007/s00500-008-0323-y

M3 - Article

AN - SCOPUS:55549103698

SN - 1432-7643

VL - 13

SP - 307

EP - 318

JO - Soft Computing

JF - Soft Computing

IS - 3

ER -

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

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Keywords

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