reg-1d

reg-1d.train

reg-1d.test

<p>Generated data set having a continuous Y variable and
a one-dimensional X variable.</p>

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.

Philipp Thomann

reg-1d: `reg-1d.train` and `reg-1d.test`

Description

Arguments

Details