The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining
Open accessAbstract
This paper introduces the 3 rd 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.
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Self-citationLearning from imbalanced data: open challenges and future directions
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A survey on semi-supervised learning
van Engelen, J. E., & Hoos, H. H. (2020) · Machine Learning · doi:10.1007/s10994-019-05855-6 · Cited by 2,666
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Metadata
- Authors
- Triguero, I., González, S., Moyano, J. M., García, S., Alcalá-Fdez, J., Luengo, J., Fernández, A., del Jesús, M. J., Sánchez, L., & Herrera, F.
- Venue
- International Journal of Computational Intelligence Systems
- Published
- 2017
- Volume
- 10
- Issue
- 1
- Pages
- 1238
- ISSN
- 1875-6883 (ISSN-L)
- OpenAlex
- W2764270061
- Cited by
- 286
- References
- 36
- FWCI
- 47.38
- Type
- journal article
- Language
- en
- Open access
- gold
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- Triguero, I., González, S., Moyano, J. M., García, S., Alcalá-Fdez, J., Luengo, J., Fernández, A., del Jesús, M. J., Sánchez, L., & Herrera, F. (2017). KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. International Journal of Computational Intelligence Systems. https://doi.org/10.2991/ijcis.10.1.82
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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