Other packages > Find by keyword >

SVMMaj  

Implementation of the SVM-Maj Algorithm
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SVMMaj", "0.2.9.4")



Attach the package and use:
library("SVMMaj")
Maintained by
Hoksan Yip
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-01-13
Latest Update: 2024-11-22
Description:
Implements the SVM-Maj algorithm to train data with support vector machine as described in Groenen et al. (2008) . This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.
How to cite:
Hoksan Yip (2011). SVMMaj: Implementation of the SVM-Maj Algorithm. R package version 0.2.9.4, https://cran.r-project.org/web/packages/SVMMaj. Accessed 29 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:25), 0.2-2 (2011-01-13 13:09), 0.2-8 (2018-02-26 01:01), 0.2.9.1 (2022-05-23 10:02), 0.2.9.2 (2024-08-19 10:20), 0.2.9.3 (2024-11-22 14:40), 0.2.9 (2019-01-26 14:10)
Other packages that cited SVMMaj R package
View SVMMaj citation profile
Other R packages that SVMMaj depends, imports, suggests or enhances
Complete documentation for SVMMaj
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
binovisualfields  
Depth-Dependent Binocular Visual Fields Simulation
Simulation and visualization depth-dependent integrated visual fields. Visual fields are measured mo ...
Download / Learn more Package Citations See dependency  
personalized2part  
Two-Part Estimation of Treatment Rules for Semi-Continuous Data
Implements the methodology of Huling, Smith, and Chen (2020) , w ...
Download / Learn more Package Citations See dependency  
fastRG  
Sample Generalized Random Dot Product Graphs in Linear Time
Samples generalized random product graphs, a generalization of a broad class of network models. Giv ...
Download / Learn more Package Citations See dependency  
GEVcdn  
GEV Conditional Density Estimation Network
Implements a flexible nonlinear modelling framework for nonstationary generalized extreme value anal ...
Download / Learn more Package Citations See dependency  

29,218

R Packages

247,686

Dependencies

77,281

Author Associations

29,219

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA