A fast gradient boosting machine covering four task types with one interface: regression (squared error), binary and multiclass classification (logistic and one-vs-rest), and right-censored survival analysis via Cox (Breslow ties), accelerated failure time (normal location-scale), or piecewise-exponential objectives. Provides native missing-value routing, baseline-hazard estimation and survival-probability prediction for the survival objectives, and deterministic multi-threaded training via 'RcppParallel'. Methods are described in Friedman (2001) <doi:10.1214/aos/1013203451>.
| Version: | 0.6.1 |
| Depends: | R (≥ 4.5.0) |
| Imports: | stats, utils, Rcpp, RcppParallel |
| LinkingTo: | Rcpp, RcppParallel |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown, survival, ggplot2, pdp, gbm, xgboost, ranger |
| Published: | 2026-09-01 |
| DOI: | 10.32614/CRAN.package.fastgbm (may not be active yet) |
| Author: | Imad El Badisy [aut, cre] |
| Maintainer: | Imad El Badisy <elbadisyimad at gmail.com> |
| BugReports: | https://github.com/ielbadisy/fastgbm/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/ielbadisy/fastgbm |
| NeedsCompilation: | yes |
| SystemRequirements: | C++17, GNU make |
| Materials: | README, NEWS |
| CRAN checks: | fastgbm results |
| Reference manual: | fastgbm.html , fastgbm.pdf |
| Vignettes: |
Algorithm (source) Benchmarking (source) Classification (source, R code) Getting Started (source, R code) Regression (source, R code) Cox, AFT, and Piecewise-Exponential Objectives (source, R code) |
| Package source: | fastgbm_0.6.1.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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