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dcsvm
View on CRAN: Click
here
Download and install dcsvm package within the R console
Install from CRAN:
install.packages("dcsvm")
Install from Github:
library("remotes")
install_github("cran/dcsvm")
Install by package version:
library("remotes")
install_version("dcsvm", "0.0.1")
Attach the package and use:
library("dcsvm")
Maintained by
Boxiang Wang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-10
Latest Update: 2025-01-10
Description:
Implements an efficient algorithm for solving sparse-penalized support vector machines with kernel density convolution. This package is designed for high-dimensional classification tasks, supporting lasso (L1) and elastic-net penalties for sparse feature selection and providing options for tuning kernel bandwidth and penalty weights. The 'dcsvm' is applicable to fields such as bioinformatics, image analysis, and text classification, where high-dimensional data commonly arise. Learn more about the methodology and algorithm at Wang, Zhou, Gu, and Zou (2023) <doi:10.1109/TIT.2022.3222767>.
How to cite:
Boxiang Wang (2025). dcsvm: Density Convoluted Support Vector Machines. R package version 0.0.1, https://cran.r-project.org/web/packages/dcsvm. Accessed 04 May. 2025.
Previous versions and publish date:
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