hdsvm: Fast Algorithm for Support Vector Machine
Implements an efficient algorithm to fit and tune penalized Support Vector Machine models using the generalized coordinate descent algorithm. Designed to handle high-dimensional datasets effectively, with emphasis on precision and computational efficiency. This package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022) <https://openreview.net/pdf?id=RvwMTDYTOb>.
| Version: |
1.0.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats, Matrix, methods |
| Suggests: |
knitr, rmarkdown |
| Published: |
2025-02-11 |
| DOI: |
10.32614/CRAN.package.hdsvm |
| Author: |
Yikai Zhang [aut, cre],
Qian Tang [aut],
Boxiang Wang [aut] |
| Maintainer: |
Yikai Zhang <yikai-zhang at uiowa.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| CRAN checks: |
hdsvm results |
Documentation:
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