Package: dcsvm
Type: Package
Title: Density Convoluted Support Vector Machines
Version: 0.0.1
Date: 2025-01-08
Authors@R: c(
  person(given = "Boxiang",
         family = "Wang",
         role = c("aut", "cre"),
         email = "boxiang-wang@uiowa.edu"),
  person(given = "Le",
         family = "Zhou",
         role = "aut"),
  person(given = "Yuwen",
         family = "Gu",
         role = "aut"),
  person(given = "Hui",
         family = "Zou",
         role = "aut"))
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>.
Depends: Matrix
Imports: grDevices, graphics, methods, stats
License: GPL-2
NeedsCompilation: yes
Encoding: UTF-8
RoxygenNote: 7.3.2
Packaged: 2026-06-11 09:42:51 UTC; root
Author: Boxiang Wang [aut, cre], Le Zhou [aut], Yuwen Gu [aut], Hui Zou
        [aut]
Maintainer: Boxiang Wang <boxiang-wang@uiowa.edu>
Repository: https://boxiang-wang.r-universe.dev
Date/Publication: 2025-01-10 21:20:02 UTC
RemoteUrl: https://github.com/cran/dcsvm
RemoteRef: HEAD
RemoteSha: 5a439b70d0dbc4ef00bb398fa774552a0c49b049