bst: Gradient Boosting

The package contains HingeBoost for binary and multi-class classification, with unequal misclassification costs for binary case. Functional gradient descent algorithm to optimize the hinge loss. The algorithm can fit linear and nonlinear classifiers.

Version: 0.3-4
Imports: rpart, gbm
Suggests: hdi
Published: 2014-06-24
Author: Zhu Wang
Maintainer: Zhu Wang <zwang at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: NA
Materials: NA
In views: MachineLearning
CRAN checks: bst results


Reference manual: bst.pdf
Package source: bst_0.3-4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: bst_0.3-4.tgz, r-oldrel: bst_0.3-4.tgz
OS X Mavericks binaries: r-release: bst_0.3-4.tgz
Old sources: bst archive

Reverse dependencies:

Reverse suggests: fscaret