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SSOSVM  

Stream Suitable Online Support Vector Machines
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SSOSVM", "0.2.1")



Attach the package and use:
library("SSOSVM")
Maintained by
Andrew Thomas Jones
[Scholar Profile | Author Map]
First Published: 2019-05-06
Latest Update: 2019-05-06
Description:
Soft-margin support vector machines (SVMs) are a common class of classification models. The training of SVMs usually requires that the data be available all at once in a single batch, however the Stochastic majorization-minimization (SMM) algorithm framework allows for the training of SVMs on streamed data instead Nguyen, Jones & McLachlan(2018)<doi:10.1007/s42081-018-0001-y>. This package utilizes the SMM framework to provide functions for training SVMs with hinge loss, squared-hinge loss, and logistic loss.
How to cite:
Andrew Thomas Jones (2019). SSOSVM: Stream Suitable Online Support Vector Machines. R package version 0.2.1, https://cran.r-project.org/web/packages/SSOSVM. Accessed 07 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited SSOSVM R package
View SSOSVM citation profile
Other R packages that SSOSVM depends, imports, suggests or enhances
Complete documentation for SSOSVM
Functions, R codes and Examples using the SSOSVM R package
Some associated functions: Hinge . Logistic . SSOSVM . SVMFit . SquareHinge . generateSim . 
Some associated R codes: RcppExports.R . Utility_functions.R .  Full SSOSVM package functions and examples
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