doi:10.2202/1557-4679.1304>, Wang (2012) <doi:10.3414/ME11-02-0020>, Wang (2018) <doi:10.1080/10618600.2018.1424635>, Wang (2018) <doi:10.1214/18-EJS1404>.">

bst: Gradient Boosting (original) (raw)

Functional gradient descent algorithm for a variety of convex and non-convex loss functions, for both classical and robust regression and classification problems. See Wang (2011) <doi:10.2202/1557-4679.1304>, Wang (2012) <doi:10.3414/ME11-02-0020>, Wang (2018) <doi:10.1080/10618600.2018.1424635>, Wang (2018) <doi:10.1214/18-EJS1404>.

Version: 0.3-24
Imports: rpart, methods, foreach, doParallel, gbm
Suggests: hdi, pROC, R.rsp, knitr, gdata
Published: 2023-01-06
DOI: 10.32614/CRAN.package.bst
Author: Zhu Wang ORCID iD [aut, cre], Torsten Hothorn [ctb]
Maintainer: Zhu Wang
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: bst citation info
Materials:
In views: MachineLearning
CRAN checks: bst results

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