From owner-cvs-ports@FreeBSD.ORG Thu Apr 23 17:02:21 2009 Return-Path: Delivered-To: cvs-ports@FreeBSD.org Received: from mx1.freebsd.org (mx1.freebsd.org [IPv6:2001:4f8:fff6::34]) by hub.freebsd.org (Postfix) with ESMTP id 254891065672; Thu, 23 Apr 2009 17:02:21 +0000 (UTC) (envelope-from miwi@FreeBSD.org) Received: from repoman.freebsd.org (repoman.freebsd.org [IPv6:2001:4f8:fff6::29]) by mx1.freebsd.org (Postfix) with ESMTP id 142068FC1A; Thu, 23 Apr 2009 17:02:21 +0000 (UTC) (envelope-from miwi@FreeBSD.org) Received: from repoman.freebsd.org (localhost [127.0.0.1]) by repoman.freebsd.org (8.14.3/8.14.3) with ESMTP id n3NH2KZO038490; Thu, 23 Apr 2009 17:02:20 GMT (envelope-from miwi@repoman.freebsd.org) Received: (from miwi@localhost) by repoman.freebsd.org (8.14.3/8.14.3/Submit) id n3NH2KtL038489; Thu, 23 Apr 2009 17:02:20 GMT (envelope-from miwi) Message-Id: <200904231702.n3NH2KtL038489@repoman.freebsd.org> From: Martin Wilke Date: Thu, 23 Apr 2009 17:02:20 +0000 (UTC) To: ports-committers@FreeBSD.org, cvs-ports@FreeBSD.org, cvs-all@FreeBSD.org X-FreeBSD-CVS-Branch: HEAD Cc: Subject: cvs commit: ports/science Makefile ports/science/py-mlpy Makefile distinfo pkg-descr pkg-plist X-BeenThere: cvs-ports@freebsd.org X-Mailman-Version: 2.1.5 Precedence: list List-Id: CVS commit messages for the ports tree List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Thu, 23 Apr 2009 17:02:21 -0000 miwi 2009-04-23 17:02:20 UTC FreeBSD ports repository Modified files: science Makefile Added files: science/py-mlpy Makefile distinfo pkg-descr pkg-plist Log: Machine Learning PY (mlpy) is a high-performance Python package for predictive modeling. It makes extensive use of numpy (http://scipy.org) to provide fast N-dimensional array manipulation and easy integration of C code. mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping.The package includes tools to measure stability in sets of ranked feature lists. WWW: http://mlpy.fbk.eu/ PR: ports/133932 Submitted by: Wen Heping Revision Changes Path 1.143 +1 -0 ports/science/Makefile 1.1 +29 -0 ports/science/py-mlpy/Makefile (new) 1.1 +3 -0 ports/science/py-mlpy/distinfo (new) 1.1 +11 -0 ports/science/py-mlpy/pkg-descr (new) 1.1 +81 -0 ports/science/py-mlpy/pkg-plist (new)