Generalized Boosted Regression Models
Overview
Extensions to Freund and Schapire's AdaBoost algorithm, Y. Freund and R. Schapire (1997) doi:10.1006/jcss.1997.1504 and Friedman's gradient boosting machine, J.H. Friedman (2001) doi:10.1214/aos/1013203451. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMART).
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK6 OK2026-05-14
Documentation
- Help pages
- 32 (1 internal)includes a package overview page
- Examples that run
- 80%4 run in a plain check · 1 hold no code
- Exported functions with examples
- 22%
- Documented parameters
- 94%
- Return-value docs
- 100%
- Help pages citing references
- 31%
Also includes 14 demo scripts (run with demo())
Downloads
Repository
- PRs merged (all time)
- 90%
- Median days to close, 50 most recently updated closed issues
- 42
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
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7 development-tooling and community-health practices detected across 4 families in the upstream repository
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Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- 3.0.2Latest
- unarchivedReturned to CRAN2026-05-13
- 3.0.12026-05-13 · diff ↗
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- archivedRemoved from CRAN2024-02-06check problems were not corrected in time
- 3.02024-01-22
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2024-01-22
- Total releases
- 3 / 2 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 1.2 MB
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