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sparseSVM  

Solution Paths of Sparse High-Dimensional Support Vector Machine with Lasso or Elastic-Net Regularization
View on CRAN: Click here


Download and install sparseSVM package within the R console
Install from CRAN:
install.packages("sparseSVM")

Install from Github:
library("remotes")
install_github("cran/sparseSVM")

Install by package version:
library("remotes")
install_version("sparseSVM", "1.1-7")



Attach the package and use:
library("sparseSVM")
Maintained by
Congrui Yi
[Scholar Profile | Author Map]
First Published: 2016-03-22
Latest Update: 2018-06-02
Description:
Fast algorithm for fitting solution paths of sparse SVM models with lasso or elastic-net regularization.
How to cite:
Congrui Yi (2016). sparseSVM: Solution Paths of Sparse High-Dimensional Support Vector Machine with Lasso or Elastic-Net Regularization. R package version 1.1-7, https://cran.r-project.org/web/packages/sparseSVM. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.1-2 (2016-03-22 23:53), 1.1-6 (2018-06-02 14:27)
Other packages that cited sparseSVM R package
View sparseSVM citation profile
Other R packages that sparseSVM depends, imports, suggests or enhances
Complete documentation for sparseSVM
Functions, R codes and Examples using the sparseSVM R package
Some associated functions: cv.sparseSVM . plot.cv.sparseSVM . plot.sparseSVM . predict.cv.sparseSVM . predict.sparseSVM . sparseSVM-package . sparseSVM . 
Some associated R codes: cv.sparseSVM.R . plot.cv.sparseSVM.R . plot.sparseSVM.R . predict.cv.sparseSVM.R . predict.sparseSVM.R . sparseSVM.R .  Full sparseSVM package functions and examples
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