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

doi:10.1007/s00500-008-0323-y

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

2008-05-22

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AI

Juan Carlos Fernández Fernández

F

Francisco Herrera

DOI：10.1007/s00500-008-0323-y

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Abstract

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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

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

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