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DESCRIPTION
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DESCRIPTION
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Package: gcdnet
Title: 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
Version: 1.0.6
Author: Yi Yang <yi.yang6@mcgill.ca>, Yuwen Gu <yuwen.gu@uconn.edu>, Hui Zou
<hzou@stat.umn.edu>
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
Imports: grDevices, graphics, stats, methods, Matrix
Description: 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.
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/emeryyi/gcdnet
Repository: CRAN
Date/Publication: 2022-08-14 02:30:02 UTC
RoxygenNote: 7.2.0
Suggests: testthat
NeedsCompilation: yes
Packaged: 2022-08-14 01:06:43 UTC; yuwen