The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
A review of unsupervised feature selection methods
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Cites
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
The WEKA data mining software: an update
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750
Elements of Information Theory
Cover, T. M., & Thomas, J. A. (2005) · doi:10.1002/047174882x · Cited by 13,791
Ant colony system: a cooperative learning approach to the traveling salesman problem
Dorigo, M., & Gambardella, L. M. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585892 · Cited by 8,081
The use of ranks to avoid the assumption of normality implicit in the analysis of variance
Friedman, M. (1937) · Journal of the American Statistical Association · doi:10.1080/01621459.1937.10503522 · Cited by 7,005
A survey on feature selection methods
Chandrashekar, G., & Sahin, F. (2014) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.11.024 · Cited by 5,189
Automatic Indexing: An Experimental Inquiry
Maron, M. E. (1961) · Journal of the ACM · doi:10.1145/321075.321084 · Cited by 570
Cited by
Malekloo, A., Ozer, E., AlHamaydeh, M., & Girolami, M. (2022) · Structural Health Monitoring · doi:10.1177/14759217211036880 · Cited by 607
Basic concepts and tools of artificial intelligence in polymer science
Ferji, K. (2025) · Polymer Chemistry · doi:10.1039/d5py00148j · Cited by 40
Enhancing Debris Flow Warning via Machine Learning Feature Reduction and Model Selection
Zhou, Q., Tang, H., Hibert, C., Chmiel, M., Walter, F., Dietze, M., & Turowski, J. M. (2025) · Journal of Geophysical Research: Earth Surface · doi:10.1029/2024jf008094 · Cited by 20
Metadata
- Authors
- Solorio-Fernández, S., Carrasco-Ochoa, J. A., & Martínez-Trinidad, J. F.
- Venue
- Artificial Intelligence Review
- Published
- 2019-01-29
- Volume
- 53
- Issue
- 2
- Pages
- 907-948
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W2911627187
- Cited by
- 648
- References
- 9
- FWCI
- 26.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Solorio-Fernández, S., Carrasco-Ochoa, J. A., & Martínez-Trinidad, J. F. (2020). A review of unsupervised feature selection methods. Artificial Intelligence Review. https://doi.org/10.1007/s10462-019-09682-y
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.
