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.

Package details

AuthorIngo Steinwart, Philipp Thomann
MaintainerPhilipp Thomann <>
Package repositoryView on CRAN
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liquidSVM documentation built on Sept. 15, 2019, 1:02 a.m.