emeryyi/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.

Getting started

Package details

AuthorYi Yang <yi.yang6@mcgill.ca>, Yuwen Gu <yuwen.gu@uconn.edu>, Hui Zou <hzou@stat.umn.edu>
MaintainerYi Yang <yi.yang6@mcgill.ca>
LicenseGPL (>= 2)
Version1.0.6
URL https://github.com/emeryyi/gcdnet
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("emeryyi/gcdnet")
emeryyi/gcdnet documentation built on Aug. 16, 2022, 7:16 a.m.