64b23ee9d0
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 <wenheping at gmail.com>
29 lines
753 B
Makefile
29 lines
753 B
Makefile
# New ports collection makefile for: py-mlpy
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# Date created: 18 April, 2009
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# Whom: Wen Heping <wenheping@gmail.com>
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#
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# $FreeBSD$
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#
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PORTNAME= mlpy
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PORTVERSION= 2.0.0
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CATEGORIES= science python
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MASTER_SITES= https://mlpy.fbk.eu/download/src/
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PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
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DISTNAME= MLPY-${PORTVERSION}
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MAINTAINER= wenheping@gmail.com
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COMMENT= High performance Python package for predictive modeling
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BUILD_DEPENDS= ${PYTHON_SITELIBDIR}/numpy:${PORTSDIR}/math/py-numpy
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RUN_DEPENDS= ${BUILD_DEPENDS}
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LIB_DEPENDS= gsl.13:${PORTSDIR}/math/gsl
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CFLAGS+= -I${LOCALBASE}/include
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LDFLAGS+= -L${LOCALBASE}/lib
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MAKE_ENV+= CFLAGS="${CFLAGS}" LDFLAGS="${LDFLAGS}"
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USE_PYTHON= yes
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USE_PYDISTUTILS= yes
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PYDISTUTILS_PKGNAME= MLPY
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.include <bsd.port.mk>
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