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l2boost
View on CRAN: Click
here
Download and install l2boost package within the R console
Install from CRAN:
install.packages("l2boost")
Install from Github:
library("remotes")
install_github("cran/l2boost")
Install by package version:
library("remotes")
install_version("l2boost", "1.0.3")
Attach the package and use:
library("l2boost")
Maintained by
John Ehrlinger
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-06-03
Latest Update: 2022-02-11
Description:
Efficient implementation of Friedman's boosting algorithm with
l2-loss function and coordinate direction (design matrix columns) basis
functions.
How to cite:
John Ehrlinger (2013). l2boost: Exploring Friedman's Boosting Algorithm for Regularized Linear Regression. R package version 1.0.3, https://cran.r-project.org/web/packages/l2boost. Accessed 01 Feb. 2025.
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Complete documentation for l2boost
Functions, R codes and Examples using
the l2boost R package
Some associated functions: VAR . coef.l2boost . cv.l2boost . diabetes . elasticNetSim . error.bars . fitted.l2boost . l2boost-package . l2boost . mvnorm.l2boost . plot.l2boost . plot.lines . predict.l2boost . print.l2boost . print.summary.l2boost . residuals.l2boost . summary.l2boost .
Some associated R codes: VAR.R . break.ties.R . coef.l2boost.R . cv.l2boost.R . diabetes.R . elasticNetSim.R . error.bars.R . eval.fold.R . extract.corr.R . fitted.l2boost.R . get.discrete.solution.R . get.hybrid.solution.R . get.lars.solution.R . help.R . l2boost.R . mstep.long.R . mvnorm.l2boost.R . nu.limit.R . plot.l2boost.R . plot.lines.R . predict.l2boost.R . print.l2boost.R . print.summary.l2boost.R . resample.R . residuals.l2boost.R . summary.l2boost.R . which.max.ind.R . which.min.ind.R . Full l2boost package functions and examples
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