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 |
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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 [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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