liquidSVM

A Fast and Versatile SVM Package

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, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

Total

6,806

Last month

609

Last week

183

Average per day

20

Daily downloads

Total downloads

Description file content

Package
liquidSVM
Type
Package
Title
A Fast and Versatile SVM Package
Version
1.2.2
Date
2019-01-10
Author
Ingo Steinwart, Philipp Thomann
Copyright
Ingo Steinwart, Philipp Thomann, Mohammad Farooq
Maintainer
Philipp Thomann
Description
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, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
URL
License
AGPL-3
Depends
R (>= 2.12.0), methods
Suggests
knitr, rmarkdown, deldir, testthat
Enhances
mlr, ParamHelpers
VignetteBuilder
knitr
RoxygenNote
6.0.1
NeedsCompilation
yes
Packaged
2019-01-10 19:28:51 UTC; philippthomann
Repository
CRAN
Date/Publication
2019-01-10 20:10:03 UTC

install.packages('liquidSVM')

1.2.2

11 days ago

https://github.com/liquidSVM/liquidSVM

Philipp Thomann

AGPL-3

Depends on

R (>= 2.12.0), methods

Suggests

knitr, rmarkdown, deldir, testthat

Discussions