Date: Sat, 13 Oct 2018 14:26:24 +0000 (UTC) From: Wen Heping <wen@FreeBSD.org> To: ports-committers@freebsd.org, svn-ports-all@freebsd.org, svn-ports-head@freebsd.org Subject: svn commit: r481987 - head/science/libsvm Message-ID: <201810131426.w9DEQO8d006429@repo.freebsd.org>
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Author: wen Date: Sat Oct 13 14:26:24 2018 New Revision: 481987 URL: https://svnweb.freebsd.org/changeset/ports/481987 Log: - Update pkg-descr PR: 232026 Submitted by: iblis@hs.ntnu.edu.tw(maintainer) Modified: head/science/libsvm/pkg-descr Modified: head/science/libsvm/pkg-descr ============================================================================== --- head/science/libsvm/pkg-descr Sat Oct 13 14:21:27 2018 (r481986) +++ head/science/libsvm/pkg-descr Sat Oct 13 14:26:24 2018 (r481987) @@ -2,14 +2,8 @@ LIBSVM is an integrated software for support vector cl nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification. -Since version 2.8, it implements an SMO-type algorithm proposed in this paper: -R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order -information for training SVM. Journal of Machine Learning Research 6, -1889-1918, 2005. You can also find a pseudo code there. - -Our goal is to help users from other fields to easily use SVM as a tool. LIBSVM -provides a simple interface where users can easily link it with their own -programs. Main features of LIBSVM include +LIBSVM provides a simple interface where users can easily link it with their +own programs. Main features of LIBSVM include * Different SVM formulations * Efficient multi-class classification
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