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Add py-liac-arff 2.4.0
The liac-arff module implements functions to read and write ARFF files in Python. It was created in the Connectionist Artificial Intelligence Laboratory (LIAC), which takes place at the Federal University of Rio Grande do Sul (UFRGS), in Brazil. ARFF (Attribute-Relation File Format) is an file format specially created for describe datasets which are used commonly for machine learning experiments and softwares. This file format was created to be used in Weka, the best representative software for machine learning automated experiments. WWW: https://github.com/renatopp/liac-arff
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svn2git
2021-03-31 03:12:20 +00:00
svn path=/head/; revision=535382
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SUBDIR += py-kim-query
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SUBDIR += py-kinematics
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SUBDIR += py-kliff
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SUBDIR += py-liac-arff
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SUBDIR += py-lifelines
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SUBDIR += py-mdp
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SUBDIR += py-mlpy
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science/py-liac-arff/Makefile
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science/py-liac-arff/Makefile
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# Created by: Po-Chuan Hsieh <sunpoet@FreeBSD.org>
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# $FreeBSD$
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PORTNAME= liac-arff
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PORTVERSION= 2.4.0
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CATEGORIES= science python
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MASTER_SITES= CHEESESHOP
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PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
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MAINTAINER= sunpoet@FreeBSD.org
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COMMENT= Read and write ARFF files in Python
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LICENSE= MIT
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TEST_DEPENDS= ${PYTHON_PKGNAMEPREFIX}mock>=0:devel/py-mock@${PY_FLAVOR}
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USES= python
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USE_PYTHON= autoplist concurrent distutils
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NO_ARCH= yes
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.include <bsd.port.mk>
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science/py-liac-arff/distinfo
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science/py-liac-arff/distinfo
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TIMESTAMP = 1588213123
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SHA256 (liac-arff-2.4.0.tar.gz) = 47afcd1fd248b2892f66075987422d0576fc2c2fd0811d0cbd32f2135b065df5
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SIZE (liac-arff-2.4.0.tar.gz) = 15276
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science/py-liac-arff/pkg-descr
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science/py-liac-arff/pkg-descr
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The liac-arff module implements functions to read and write ARFF files in
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Python. It was created in the Connectionist Artificial Intelligence Laboratory
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(LIAC), which takes place at the Federal University of Rio Grande do Sul
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(UFRGS), in Brazil.
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ARFF (Attribute-Relation File Format) is an file format specially created for
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describe datasets which are used commonly for machine learning experiments and
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softwares. This file format was created to be used in Weka, the best
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representative software for machine learning automated experiments.
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WWW: https://github.com/renatopp/liac-arff
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