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bst  

Gradient Boosting
View on CRAN: Click here


Download and install bst package within the R console
Install from CRAN:
install.packages("bst")

Install from Github:
library("remotes")
install_github("cran/bst")

Install by package version:
library("remotes")
install_version("bst", "0.3-24")



Attach the package and use:
library("bst")
Maintained by
Zhu Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-03-31
Latest Update: 2023-01-06
Description:
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) , Wang (2012) , Wang (2018) , Wang (2018) .
How to cite:
Zhu Wang (2011). bst: Gradient Boosting. R package version 0.3-24, https://cran.r-project.org/web/packages/bst. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.2 (2011-03-31 17:18), 0.3-1 (2011-06-24 18:58), 0.3-2 (2012-01-17 21:52), 0.3-3 (2013-09-12 17:47), 0.3-4 (2014-06-24 01:03), 0.3-11 (2015-12-19 11:02), 0.3-12 (2016-01-04 17:46), 0.3-13 (2016-02-28 09:59), 0.3-14 (2016-09-21 16:05), 0.3-15 (2018-07-23 22:40), 0.3-16 (2019-01-16 10:10), 0.3-17 (2019-02-27 18:00), 0.3-20 (2020-05-01 00:00), 0.3-21 (2020-06-02 18:00), 0.3-22 (2020-10-19 19:20), 0.3-23 (2020-11-09 23:10)
Other packages that cited bst R package
View bst citation profile
Other R packages that bst depends, imports, suggests or enhances
Complete documentation for bst
Functions, R codes and Examples using the bst R package
Some associated functions: bfunc . bst-internal . bst . bst.sel . bst_control . cv.bst . cv.mada . cv.mbst . cv.mhingebst . cv.mhingeova . cv.rbst . cv.rmbst . evalerr . ex1data . mada . mbst . mhingebst . mhingeova . nsel.mhingebst . rbst . rbstpath . rmbst . 
Some associated R codes: balanced.folds.R . bst.R . fpartial.R . mada.R . mbst.R . mhingebst.R . mhingeova.R . permute.rows.R . rbst.R . rmbst.R . simdata.R .  Full bst package functions and examples
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