Package: l2boost 1.0.3

l2boost: Exploring Friedman's Boosting Algorithm for Regularized Linear Regression

Efficient implementation of Friedman's boosting algorithm with l2-loss function and coordinate direction (design matrix columns) basis functions.

Authors:John Ehrlinger [aut, cre], Hemant Ishwaran [aut]

l2boost_1.0.3.tar.gz
l2boost_1.0.3.zip(r-4.7)l2boost_1.0.3.zip(r-4.6)l2boost_1.0.3.zip(r-4.5)
l2boost_1.0.3.tgz(r-4.6-any)l2boost_1.0.3.tgz(r-4.5-any)
l2boost_1.0.3.tar.gz(r-4.7-any)l2boost_1.0.3.tar.gz(r-4.6-any)
l2boost_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
l2boost/json (API)

# Install 'l2boost' in R:
install.packages('l2boost', repos = c('https://ehrlinger.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ehrlinger/l2boost/issues

Datasets:
  • diabetes - Blood and other measurements in diabetics [Hastie and Efron (2012)]

On CRAN:

Conda:

3.48 score 6 stars 10 scripts 201 downloads 4 exports 1 dependencies

Last updated from:b924457c5f. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE147
source / vignettesOK206
linux-release-x86_64NOTE147
macos-release-arm64NOTE102
macos-oldrel-arm64NOTE112
windows-develNOTE75
windows-releaseNOTE76
windows-oldrelNOTE72
wasm-releaseOK109

Exports:cv.l2boostelasticNetSiml2boostmvnorm.l2boost

Dependencies:MASS

Readme and manuals

Help Manual

Help pageTopics
Efficient implementation of Friedman's boosting algorithm for linear regression using an l2-loss function and coordinate direction (design matrix columns) basis functions.l2boost-package
Extract model coefficients from an l2boost model object at any point along the solution path indexed by step m. 'coef' is a generic function which extracts model coefficients from objects returned by modeling functions.coef.l2boost
K-fold cross-validation using 'l2boost'.cv.l2boost
Blood and other measurements in diabetics [Hastie and Efron (2012)]diabetes
A blocked correlated data simulation.elasticNetSim
nice standard errors for plotserror.bars
Extract the fitted model estimates along the solution path for an l2boost model.fitted.l2boost
Generic gradient descent boosting method for linear regression.l2boost l2boost.default l2boost.formula
multivariate normal data simulations.mvnorm.l2boost
Plotting for 'l2boost' objects.plot.l2boost
plots.lines is used by 'plot.l2boost' to the path lines (each j, against each r-step)plot.lines
predict method for l2boost models.predict.l2boost
print method for 'l2boost' and 'cv.l2boost' objects.print.l2boost
Unimplemented generic function These are placeholders right now.print.summary.l2boost
Model residuals for the training set of an l2boost model objectresiduals.l2boost
Unimplemented generic function These are placeholders right now.summary.l2boost
This is a hidden function of the l2boost package. VAR is a helper function that specifically returns NA if all values of the argument x are NA, otherwise, it returns a var object.VAR