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KEEL: a software tool to assess evolutionary algorithms for data mining problems
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DOI：10.1007/s00500-008-0323-y.png)
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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.
Keyword:
Computer-based education
Data mining
Evolutionary computation
Experimental design
Graphical programming
Java
Knowledge extraction
Machine learning
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2.5
论文数:
1.0W
被引数:
2.1W
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