Fast Histogram Gradient Boosting for Regression, Classification, and Survival Analysis R package fastgbm version 0.6.1 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>. Software 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 Imad El Badisy <elbadisyimad@gmail.com> Comprehensive R Archive Network (CRAN) Imad El Badisy [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=fastgbm/LICENSE) 2026-09-01 application/tgz https://CRAN.R-project.org/package=fastgbm doi:10.32614/CRAN.package.fastgbm