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gbm: Generalized Boosted Regression Models
Open accessAbstract
An implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway. Newer version available at github.com/gbm-developers/gbm3.
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Cited by
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Apley, D. W., & Zhu, J. (2020) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/rssb.12377 · Cited by 1,535
Schratz, P., Muenchow, J., Iturritxa, E., Richter, J., & Brenning, A. (2019) · Ecological Modelling · doi:10.1016/j.ecolmodel.2019.06.002 · Cited by 614
Norberg, A., Abrego, N., Blanchet, F. G., Adler, F. R., Anderson, B. J., Anttila, J., Araújo, M. B., Dallas, T., Dunson, D., Elith, J., et al. (2019) · Ecological Monographs · doi:10.1002/ecm.1370 · Cited by 573
The Evolution of Boosting Algorithms: From Machine Learning to Statistical Modelling
Binder, H., Gefeller, O., Schmid, M., & Mayr, A. (2014) · Methods of Information in Medicine · doi:10.3414/me13-01-0122 · Cited by 412
Zhong, X., Chen, Z., Li, Y., Ding, K., Liu, W., Liu, Y., Yuan, Y., Zhang, M., Baker, A. J. M., Yang, W., et al. (2020) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2020.123289 · Cited by 365
Metadata
- Authors
- Ridgeway, G., & Developers, G.
- Venue
- CRAN: Contributed Packages
- Publisher
- The R Foundation
- Published
- 2003-02-21
- OpenAlex
- W4399650065
- Cited by
- 555
- References
- 0
- Type
- dataset
- Language
- en
- Open access
- gold
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