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SSOSVM

Stream Suitable Online Support Vector Machines

v0.2.2 · Sep 20, 2025 · GPL-3

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.

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r-devel-linux-x86_64-debian-gcc OK
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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
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r-patched-linux-x86_64 OK
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r-release-macos-arm64 OK
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r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies Rcpp mvtnorm SSOSVM

Version History

new 0.2.2 Mar 10, 2026
updated 0.2.2 ← 0.2.1 diff Sep 19, 2025
new 0.2.1 May 5, 2019