Package: gcdnet 1.0.6

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
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gcdnet.pdf |gcdnet.html
gcdnet/json (API)

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

Peer review:

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:

9 exports 7 stars 2.15 score 2 dependencies 2 dependents 3 mentions 63 scripts 370 downloads

Last updated 2 years agofrom:4795e90438. Checks:OK: 1 ERROR: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-win-x86_64ERRORSep 13 2024
R-4.5-linux-x86_64ERRORSep 13 2024
R-4.4-win-x86_64ERRORSep 13 2024
R-4.4-mac-x86_64ERRORSep 13 2024
R-4.4-mac-aarch64ERRORSep 13 2024
R-4.3-win-x86_64ERRORSep 13 2024
R-4.3-mac-x86_64ERRORSep 13 2024
R-4.3-mac-aarch64ERRORSep 13 2024

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

Dependencies:latticeMatrix