Metadata-Version: 2.0
Name: liquidSVM
Version: 1.0
Summary: 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.
Home-page: http://www.isa.uni-stuttgart.de/software/
Author: Ingo Steinwart, Philipp Thomann
Author-email: philipp.thomann@mathematik.uni-stuttgart.de
License: AGPL v3
Platform: UNKNOWN
Requires-Dist: numpy

UNKNOWN


