Fast Artificial Neural Network Library is a free open source neural network
library, which implements multilayer artificial neural networks in C with
support for both fully connected and sparsely connected networks.
Cross-platform execution in both fixed and floating point are supported. It
includes a framework for easy handling of training data sets. It is easy to
use, versatile, well documented, and fast. PHP, C++, .NET, Ada, Python, Delphi,
Octave, Ruby, Pure Data and Mathematica bindings are available. A reference
manual accompanies the library with examples and recommendations on how to use
the library. A graphical user interface is also available for the library.
WWW: http://leenissen.dk/fann/
PR: ports/109853
Submitted by: Tz-Huan Huang <tzhuan at csie.org>
2007-03-06 20:15:43 +01:00
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# New ports collection makefile for: fann
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# Date created: 2007-03-04
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# Whom: Tz-Huan Huang <tzhuan@csie.org>
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#
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# $FreeBSD$
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#
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PORTNAME= fann
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PORTVERSION= 2.1.0b
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CATEGORIES= math science
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2009-08-22 02:28:34 +02:00
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MASTER_SITES= SF/${PORTNAME}/${PORTNAME}/${PORTVERSION}eta
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Fast Artificial Neural Network Library is a free open source neural network
library, which implements multilayer artificial neural networks in C with
support for both fully connected and sparsely connected networks.
Cross-platform execution in both fixed and floating point are supported. It
includes a framework for easy handling of training data sets. It is easy to
use, versatile, well documented, and fast. PHP, C++, .NET, Ada, Python, Delphi,
Octave, Ruby, Pure Data and Mathematica bindings are available. A reference
manual accompanies the library with examples and recommendations on how to use
the library. A graphical user interface is also available for the library.
WWW: http://leenissen.dk/fann/
PR: ports/109853
Submitted by: Tz-Huan Huang <tzhuan at csie.org>
2007-03-06 20:15:43 +01:00
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DISTNAME= fann-2.1.0beta
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MAINTAINER= tzhuan@csie.org
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COMMENT= A free open source neural network library
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WRKSRC= ${WRKDIR}/fann-2.1.0
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USE_ZIP= yes
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GNU_CONFIGURE= yes
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USE_LDCONFIG= yes
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.include <bsd.port.mk>
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