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hdsvm (version 1.0.2)

Fast Algorithm for Support Vector Machine

Description

Implements an efficient algorithm for fitting the entire regularization path of support vector machine models with elastic-net penalties using a generalized coordinate descent scheme. The framework also supports SCAD and MCP penalties. It is designed for high-dimensional datasets and emphasizes numerical accuracy and computational efficiency. This package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022) .

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Version

Install

install.packages('hdsvm')

Monthly Downloads

147

Version

1.0.2

License

GPL-2

Maintainer

Yikai Zhang

Last Published

September 26th, 2025

Functions in hdsvm (1.0.2)

coef.cv.hdsvm

Extract Coefficients from a `cv.hdsvm` Object
cv.hdsvm

Cross-validation for Selecting the Tuning Parameter in the Penalized SVM
coef.nc.hdsvm

Extract Model Coefficients from a `nc.hdsvm` Object
coef.cv.nc.hdsvm

Extract Coefficients from a `cv.nc.hdsvm` Object
predict.cv.hdsvm

Make Predictions from a `cv.hdsvm` Object
predict.cv.nc.hdsvm

Make Predictions from a `cv.nc.hdsvm` Object
coef.hdsvm

Extract Model Coefficients from a `hdsvm` Object
predict.nc.hdsvm

Make Predictions from a `nc.hdsvm` Object
predict.hdsvm

Make Predictions from a `hdsvm` Object
nc.hdsvm

Solve the Penalized SVM with Nonconvex Penalties
hdsvm

Solve Penalized SVM
cv.nc.hdsvm

Cross-validation for Selecting the Tuning Parameter of Nonconvex Penalized SVM