liquidSVM (

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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.

Maintainer: ORPHANED
Author(s): Ingo Steinwart, Philipp Thomann

License: AGPL-3

Uses: deldir, testthat, knitr, rmarkdown
Enhances: ParamHelpers, mlr
Reverse suggests: mlr

Released 6 months ago.

4 previous versions



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