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KEEL 3.0: an open source software for multi-stage analysis in data mining

Triguero, Isaac; González, Sergio; Moyano, Jose M.; García, Salvador; Alcalá-Fdez, Jesús; Luengo, Julian; Fernández, Alberto; del Jesús, Maria José; Sánchez, Luciano; Herrera, Francisco

Authors

Isaac Triguero Isaac.Triguero@nottingham.ac.uk

Sergio González

Jose M. Moyano

Salvador García

Jesús Alcalá-Fdez

Julian Luengo

Alberto Fernández

Maria José del Jesús

Luciano Sánchez

Francisco Herrera



Abstract

This paper introduces the 3rd major release of the KEEL Software. KEEL is an open source Java framework (GPLv3 license) that provides a number of modules to perform a wide variety of data mining tasks. It includes tools to performdata management, design of multiple kind of experiments, statistical analyses, etc. This framework also contains KEEL-dataset, a data repository for multiple learning tasks featuring data partitions and algorithms’ results over these problems. In this work, we describe the most recent components added to KEEL 3.0, including new modules for semi-supervised learning, multi-instance learning, imbalanced classification and subgroup discovery. In addition, a new interface in R has been incorporated to execute algorithms included in KEEL. These new features greatly improve the versatility of KEEL to deal with more modern data mining problems.

Journal Article Type Article
Publication Date Sep 26, 2017
Journal International Journal of Computational Intelligence Systems
Print ISSN 1875-6891
Electronic ISSN 1875-6883
Publisher Taylor & Francis Open
Peer Reviewed Peer Reviewed
Volume 10
Issue 1
APA6 Citation Triguero, I., González, S., Moyano, J. M., García, S., Alcalá-Fdez, J., Luengo, J., …Herrera, F. (2017). KEEL 3.0: an open source software for multi-stage analysis in data mining. International Journal of Computational Intelligence Systems, 10(1), https://doi.org/10.2991/ijcis.10.1.82
DOI https://doi.org/10.2991/ijcis.10.1.82
Keywords Open Source, Java, Data Mining, Preprocessing, Evolutionary Algorithms
Publisher URL http://www.atlantis-press.com/journals/ijcis/25883592
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc/4.0





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