From owner-freebsd-ports Tue Dec 18 18:30:31 2001 Delivered-To: freebsd-ports@hub.freebsd.org Received: from freefall.freebsd.org (freefall.FreeBSD.org [216.136.204.21]) by hub.freebsd.org (Postfix) with ESMTP id 6ADC237B41C for ; Tue, 18 Dec 2001 18:30:04 -0800 (PST) Received: (from gnats@localhost) by freefall.freebsd.org (8.11.6/8.11.6) id fBJ2U4X24183; Tue, 18 Dec 2001 18:30:04 -0800 (PST) (envelope-from gnats) Received: from ob.m6.ntu.edu.tw (ob.m6.ntu.edu.tw [140.112.247.129]) by hub.freebsd.org (Postfix) with ESMTP id 9D76237B416 for ; Tue, 18 Dec 2001 18:27:23 -0800 (PST) Received: from davidyu by ob.m6.ntu.edu.tw with local (Exim 3.33 #1) id 16GWRt-00026t-00 for FreeBSD-gnats-submit@freebsd.org; Wed, 19 Dec 2001 10:27:13 +0800 Message-Id: Date: Wed, 19 Dec 2001 10:27:13 +0800 From: Chia-Hsing Yu Reply-To: Chia-Hsing Yu To: FreeBSD-gnats-submit@freebsd.org X-Send-Pr-Version: 3.113 Subject: ports/32997: new ports for libsvm Sender: owner-freebsd-ports@FreeBSD.ORG Precedence: bulk List-ID: List-Archive: (Web Archive) List-Help: (List Instructions) List-Subscribe: List-Unsubscribe: X-Loop: FreeBSD.org >Number: 32997 >Category: ports >Synopsis: new ports for libsvm >Confidential: no >Severity: non-critical >Priority: low >Responsible: freebsd-ports >State: open >Quarter: >Keywords: >Date-Required: >Class: update >Submitter-Id: current-users >Arrival-Date: Tue Dec 18 18:30:00 PST 2001 >Closed-Date: >Last-Modified: >Originator: Chia-Hsing Yu >Release: FreeBSD 4.4-STABLE i386 >Organization: NTU CSIE >Environment: System: FreeBSD ob.m6.ntu.edu.tw 4.4-STABLE FreeBSD 4.4-STABLE #0: Mon Dec 17 11:23:27 CST 2001 root@ob.m6.ntu.edu.tw:/usr/src/sys/compile/OB i386 >Description: LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC ), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM ). It supports multi-class classification. The basic algorithm is a simplification of both SMO by Platt and SVMLight by Joachims. It is also a simplification of the modification 2 of SMO by Keerthi et al. 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 Different SVM formulations Efficient multi-class classification Cross validation for model selection Weighted SVM for unbalanced data Both C++ and Java sources GUI demonstrating SVM classification and regression http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Author: Chih-Chung Chang and Chih-Jen Lin >How-To-Repeat: >Fix: please fetch http://www.oio.cx/~davidyu/libsvm.tgz >Release-Note: >Audit-Trail: >Unformatted: To Unsubscribe: send mail to majordomo@FreeBSD.org with "unsubscribe freebsd-ports" in the body of the message