The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
A new variable selection approach using Random Forests
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Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Modern Applied Statistics with S
Venables, W. N., & Ripley, B. D. (2002) · Statistics and Computing · doi:10.1007/978-0-387-21706-2 · Cited by 24,305
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
UCI Machine Learning Repository
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Cited by
A comparison of random forest variable selection methods for classification prediction modeling
Speiser, J. L., Miller, M. E., Tooze, J., & Ip, E. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.05.028 · Cited by 1,561
Analysis of machine learning techniques for heart failure readmissions
Mortazavi, B. J., Downing, N. S., Bucholz, E. M., Dharmarajan, K., Manhapra, A., Li, S.-X., Negahban, S. N., & Krumholz, H. M. (2016) · Circulation: Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.116.003039 · Cited by 401
Jaxa-Rozen, M., & Kwakkel, J. (2018) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2018.06.011 · Cited by 91
Everson, T. M., Lyons, G., Zhang, H., Soto-Ramírez, N., Lockett, G. A., Patil, V. K., Merid, S. K., Sӧderhӓll, C., Melén, E., Holloway, J. W., et al. (2015) · Genome Medicine · doi:10.1186/s13073-015-0213-8 · Cited by 78
Metadata
- Authors
- Hapfelmeier, A., & Ulm, K.
- Venue
- Computational Statistics & Data Analysis
- Publisher
- Elsevier BV
- Published
- 2013-04
- Volume
- 60
- Pages
- 50-69
- ISSN
- 0167-9473 (ISSN-L)
- OpenAlex
- W1979279626
- Cited by
- 259
- References
- 61
- FWCI
- 10.79
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: A new variable selection approach using Random Forests. https://app.cochat.ai/papers/10.1016/j.csda.2012.09.020
- The paper
- Hapfelmeier, A., & Ulm, K. (2013). A new variable selection approach using Random Forests. Computational Statistics & Data Analysis. https://doi.org/10.1016/j.csda.2012.09.020
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.
