Package: gcdnet 1.0.6

Yi Yang

gcdnet: The (Adaptive) LASSO and Elastic Net Penalized Least Squares, Logistic Regression, Hybrid Huberized Support Vector Machines, Squared Hinge Loss Support Vector Machines and Expectile Regression using a Fast Generalized Coordinate Descent Algorithm

Implements a generalized coordinate descent (GCD) algorithm for computing the solution paths of the hybrid Huberized support vector machine (HHSVM) and its generalizations. Supported models include the (adaptive) LASSO and elastic net penalized least squares, logistic regression, HHSVM, squared hinge loss SVM and expectile regression.

Authors:Yi Yang <[email protected]>, Yuwen Gu <[email protected]>, Hui Zou <[email protected]>

gcdnet_1.0.6.tar.gz
gcdnet_1.0.6.tar.gz(r-4.7-arm64)gcdnet_1.0.6.tar.gz(r-4.7-x86_64)gcdnet_1.0.6.tar.gz(r-4.6-arm64)gcdnet_1.0.6.tar.gz(r-4.6-x86_64)
gcdnet_1.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
gcdnet/json (API)

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

Bug tracker:https://github.com/emeryyi/gcdnet/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • FHT - FHT data introduced in Friedman et al. (2010).

On CRAN:

Conda:

fortran

4.23 score 6 packages 77 scripts 4.1k downloads 3 mentions 9 exports 2 dependencies

Last updated from:4e14d2e326. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK127
linux-devel-x86_64OK122
source / vignettesOK174
linux-release-arm64OK143
linux-release-x86_64OK125
wasm-releaseOK107

Exports:coefcv.erpathcv.gcdnetcv.hsvmpathcv.logitpathcv.lspathcv.sqsvmpathgcdnetpredict

Dependencies:latticeMatrix