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Machine learning and data mining
Overview
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Citations
Cited by
Predicting academic success in higher education: literature review and best practices
Alyahyan, E., & Düştegör, D. (2020) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-020-0177-7 · Cited by 615
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning
Garcia, S., Luengo, J., Sáez, J. A., López, V., & Herrera, F. (2013) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2012.35 · Cited by 548
A review of deep learning applications for genomic selection
Montesinos-López, O. A., Montesinos-López, A., Pérez-Rodríguez, P., Barrón-López, J. A., Martini, J. W. R., Fajardo-Flores, S. B., Gaytan-Lugo, L. S., Santana-Mancilla, P. C., & Crossa, J. (2021) · BMC Genomics · doi:10.1186/s12864-020-07319-x · Cited by 361
“could not be incorporated into a parametric model at the beginning [34].”
BackgroundHybrid approaches to optimization and machine learning methods: a systematic literature review
Azevedo, B. F., Rocha, A. M. A. C., & Pereira, A. I. (2024) · Machine Learning · doi:10.1007/s10994-023-06467-x · Cited by 291
A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification
Triguero, I., Derrac, J., Garcia, S., & Herrera, F. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2010.2103939 · Cited by 269
Metadata
- Authors
- Kononenko, I., & Kukar, M.
- Venue
- Woodhead Publishing Limited eBooks
- Publisher
- Woodhead Publishing Limited
- Published
- 2007
- OpenAlex
- W3149365120
- Cited by
- 293
- References
- 0
- FWCI
- 11.44
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Machine learning and data mining. https://app.cochat.ai/papers/10.1533/9780857099440
- The paper
- Kononenko, I., & Kukar, M. (2007). Machine learning and data mining. Woodhead Publishing Limited eBooks. https://doi.org/10.1533/9780857099440
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
