Details

Autor(en) / Beteiligte

• Alcalá-Fdez, J.
• Sánchez, L.
• García, S.
• del Jesus, M. J.
• Ventura, S.
• Garrell, J. M.
• Otero, J.
• Romero, C.
• Bacardit, J.
• Rivas, V. M.
• Fernández, J. C.
• Herrera, F.

Titel

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

Ist Teil von

• Soft computing (Berlin, Germany), 2009-02, Vol.13 (3), p.307-318

Ort / Verlag

Berlin/Heidelberg: Springer-Verlag

Erscheinungsjahr

2009

Quelle

SpringerLink

Beschreibungen/Notizen

• 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.