Package: bst 0.3-24

bst: Gradient Boosting

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>.

Authors:Zhu Wang [aut, cre], Torsten Hothorn [ctb]

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bst_0.3-24.tgz(r-4.6-any)bst_0.3-24.tgz(r-4.5-any)
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bst_0.3-24.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bst/json (API)

# Install 'bst' in R:
install.packages('bst', repos = c('https://zhuwang46.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.43 score 1 stars 6 packages 42 scripts 5.0k downloads 38 exports 9 dependencies

Last updated from:53dbd049b0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK137
source / vignettesOK198
linux-release-x86_64OK128
macos-release-arm64OK127
macos-oldrel-arm64OK94
windows-develOK108
windows-releaseOK103
windows-oldrelOK102
wasm-releaseOK99

Exports:balanced.foldsbfuncbstbst_controlbst.selcv.bstcv.madacv.mbstcv.mhingebstcv.mhingeovacv.rbstcv.rmbstevalerrex1datafpartial.bstfpartial.mbstfpartial.mhingebstgausslossgaussngragradienthingelosshingengralossloss.mbstloss.mhingebstmadambstmbst_fitmhingebstmhingebst_fitmhingeovangradientnselpermute.rowsplotCVbstrbstrbstpathrmbst

Dependencies:codetoolsdoParallelforeachgbmiteratorslatticeMatrixrpartsurvival

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Started: 2016-01-04