Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non- parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, inclusion of a variety of different classification and regression scenarios, and full flexibility for experts.

Documentation

Manual: liquidSVM.pdf
Vignettes:

Maintainer: Philipp Thomann <philipp.thomann at mathematik.uni-stuttgart.de>

Author(s): Ingo Steinwart, Philipp Thomann

Install package and any missing dependencies by running this line in your R console:

install.packages("liquidSVM")

Depends R (>= 2.12.0), methods
Imports
Suggests knitr, rmarkdown, deldir, testthat
Enhances mlr, ParamHelpers
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Package liquidSVM
Materials
URL http://www.isa.uni-stuttgart.de/software/R
Task Views
Version 1.0.1
Published 2017-03-02
License AGPL-3
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks liquidSVM check results
Package source liquidSVM_1.0.1.tar.gz