gbm3
3.0.2Generalized 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
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-05-146 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 94%
- Return-value docs
- 100%
- References docs
- 31%
Downloads
Repository
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Repository practices
3 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/gbm-developers/gbm3 on 2026-08-23.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- 3.0.2Latest
- 3.0.12026-05-14 · diff ↗
- unarchivedReturned to CRAN2026-05-13
- 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
- 2026-05-14
- Total releases
- 3 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 1.2 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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