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This package includes a scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning. These Relief-Based algorithms (RBAs) are designed for feature weighting/selection as part of a machine learning pipeline (supervised learning). Presently this includes the following core RBAs: ReliefF, SURF, SURF*, MultiSURF*, and MultiSURF. Additionally, an implementation of the iterative TuRF mechanism and VLSRelief is included. WWW: https://github.com/EpistasisLab/scikit-rebate
25 lines
632 B
Makefile
25 lines
632 B
Makefile
# Created by: Po-Chuan Hsieh <sunpoet@FreeBSD.org>
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PORTNAME= skrebate
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PORTVERSION= 0.62
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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= Relief-based feature selection algorithms
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LICENSE= MIT
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LICENSE_FILE= ${WRKSRC}/LICENSE
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RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}scikit-learn>=0:science/py-scikit-learn@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}scipy>=0:science/py-scipy@${PY_FLAVOR}
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USES= python:3.6+
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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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