KEEL 3.0: an open source software for multi-stage analysis in data mining
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 a...
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| Format: | Article |
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Atlantis Press
2017
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| Online Access: | https://eprints.nottingham.ac.uk/46280/ |
| _version_ | 1848797293888667648 |
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| author | Triguero, Isaac González, Sergio Moyano, Jose M. García, Salvador Alcalá-Fdez, Jesús Luengo, Julian Fernández, Alberto del Jesús, Maria José Sánchez, Luciano Herrera, Francisco |
| author_facet | Triguero, Isaac González, Sergio Moyano, Jose M. García, Salvador Alcalá-Fdez, Jesús Luengo, Julian Fernández, Alberto del Jesús, Maria José Sánchez, Luciano Herrera, Francisco |
| author_sort | Triguero, Isaac |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:01:35Z |
| format | Article |
| id | nottingham-46280 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:01:35Z |
| publishDate | 2017 |
| publisher | Atlantis Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-462802020-05-04T19:08:49Z https://eprints.nottingham.ac.uk/46280/ 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 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. Atlantis Press 2017-09-26 Article PeerReviewed Triguero, Isaac, González, Sergio, Moyano, Jose M., García, Salvador, Alcalá-Fdez, Jesús, Luengo, Julian, Fernández, Alberto, del Jesús, Maria José, Sánchez, Luciano and Herrera, Francisco (2017) KEEL 3.0: an open source software for multi-stage analysis in data mining. International Journal of Computational Intelligence Systems, 10 (1). pp. 1238-1249. ISSN 1875-6883 Open Source Java Data Mining Preprocessing Evolutionary Algorithms http://www.atlantis-press.com/journals/ijcis/25883592 doi:10.2991/ijcis.10.1.82 doi:10.2991/ijcis.10.1.82 |
| spellingShingle | Open Source Java Data Mining Preprocessing Evolutionary Algorithms Triguero, Isaac González, Sergio Moyano, Jose M. García, Salvador Alcalá-Fdez, Jesús Luengo, Julian Fernández, Alberto del Jesús, Maria José Sánchez, Luciano Herrera, Francisco KEEL 3.0: an open source software for multi-stage analysis in data mining |
| title | KEEL 3.0: an open source software for multi-stage analysis in data mining |
| title_full | KEEL 3.0: an open source software for multi-stage analysis in data mining |
| title_fullStr | KEEL 3.0: an open source software for multi-stage analysis in data mining |
| title_full_unstemmed | KEEL 3.0: an open source software for multi-stage analysis in data mining |
| title_short | KEEL 3.0: an open source software for multi-stage analysis in data mining |
| title_sort | keel 3.0: an open source software for multi-stage analysis in data mining |
| topic | Open Source Java Data Mining Preprocessing Evolutionary Algorithms |
| url | https://eprints.nottingham.ac.uk/46280/ https://eprints.nottingham.ac.uk/46280/ https://eprints.nottingham.ac.uk/46280/ |