International Journal of Computational Intelligence Systems

Volume 10, Issue 1, 2017, Pages 1238 - 1249

KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

Authors
Isaac Triguero1, Isaac.Triguero@nottingham.ac.uk, Sergio González2, Jose M. Moyano4, Salvador García2, Jesús Alcalá-Fdez2, Julián Luengo2, Alberto Fernández2, Maria José del Jesús5, Luciano Sánchez3, Francisco Herrera2
1School of Computer Science, University of Nottingham, Jubilee Campus, Nottingham NG8 1BB, United Kingdom
2Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain, 18071
3Department of Computer Science, University of Oviedo, Gijón, 33204, Spain
4Department of Computer Science and Numerical Analysis, University of Cordoba, 14071 Cordoba, Spain
5Department of Computer Science, University of Jaén, Jaén, Spain
Received 6 March 2017, Accepted 9 September 2017, Available Online 25 September 2017.
DOI
https://doi.org/10.2991/ijcis.10.1.82How to use a DOI?
Keywords
Open Source, Java, Data Mining, Preprocessing, Evolutionary Algorithms
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 perform data 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.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
10 - 1
Pages
1238 - 1249
Publication Date
2017/09
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.10.1.82How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Isaac Triguero
AU  - Sergio González
AU  - Jose M. Moyano
AU  - Salvador García
AU  - Jesús Alcalá-Fdez
AU  - Julián Luengo
AU  - Alberto Fernández
AU  - Maria José del Jesús
AU  - Luciano Sánchez
AU  - Francisco Herrera
PY  - 2017
DA  - 2017/09
TI  - KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining
JO  - International Journal of Computational Intelligence Systems
SP  - 1238
EP  - 1249
VL  - 10
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.10.1.82
DO  - https://doi.org/10.2991/ijcis.10.1.82
ID  - Triguero2017
ER  -