Package: fastgbm
Type: Package
Title: Fast Histogram Gradient Boosting for Regression, Classification,
        and Survival Analysis
Version: 0.7.0
Authors@R: person("Imad", "El Badisy", email = "elbadisyimad@gmail.com", role = c("aut", "cre"))
Description: 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, and competing risks via
        Fine-Gray subdistribution hazards, cause-specific hazards, or
        coupled cause-specific hazards, following 'CoxBoost' (Binder et
        al. 2009) <doi:10.1093/bioinformatics/btp088>. 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>.
License: MIT + file LICENSE
URL: https://github.com/ielbadisy/fastgbm
BugReports: https://github.com/ielbadisy/fastgbm/issues
Encoding: UTF-8
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, CoxBoost
VignetteBuilder: knitr
Config/testthat/edition: 3
SystemRequirements: C++17, GNU make
RoxygenNote: 7.3.3
Config/pak/sysreqs: cmake make
Repository: https://ielbadisy.r-universe.dev
Date/Publication: 2026-10-11 16:47:09 UTC
RemoteUrl: https://github.com/ielbadisy/fastgbm
RemoteRef: HEAD
RemoteSha: 622f37d9a0df9ec3767379a811eca4fb117c9059
NeedsCompilation: yes
Packaged: 2026-10-11 20:29:45 UTC; root
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>