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New port: science/py-GPyOpt: Bayesian optimization toolbox based on GPy
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svn2git
2021-03-31 03:12:20 +00:00
svn path=/head/; revision=487730
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SUBDIR += pulseview
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SUBDIR += py-DendroPy
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SUBDIR += py-GPy
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SUBDIR += py-GPyOpt
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SUBDIR += py-PyFR
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SUBDIR += py-lifelines
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SUBDIR += py-MDAnalysis
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science/py-GPyOpt/Makefile
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science/py-GPyOpt/Makefile
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# $FreeBSD$
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PORTNAME= GPyOpt
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DISTVERSION= 1.2.5
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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= yuri@FreeBSD.org
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COMMENT= Bayesian optimization toolbox based on GPy
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LICENSE= BSD3CLAUSE
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LICENSE_FILE= ${WRKSRC}/LICENSE.txt
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RUN_DEPENDS= ${PYNUMPY} \
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${PYTHON_PKGNAMEPREFIX}scipy>=0.16:science/py-scipy@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}GPy>=1.8>0:science/py-GPy@${PY_FLAVOR}
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USES= python
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USE_PYTHON= distutils concurrent autoplist
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NO_ARCH= yes
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.include <bsd.port.mk>
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science/py-GPyOpt/distinfo
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science/py-GPyOpt/distinfo
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TIMESTAMP = 1545114436
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SHA256 (GPyOpt-1.2.5.tar.gz) = f92276dd47dc5129ca3e83f6604e4f902a845bbd3226d9c2c6a2f6b942973a18
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SIZE (GPyOpt-1.2.5.tar.gz) = 55158
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science/py-GPyOpt/pkg-descr
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science/py-GPyOpt/pkg-descr
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GPyOpt is a Python open-source library for Bayesian Optimization developed by
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the Machine Learning group of the University of Sheffield. It is based on GPy,
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a Python framework for Gaussian process modelling.
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With GPyOpt you can:
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* Automatically configure your models and Machine Learning algorithms.
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* Design your wet-lab experiments saving time and money.
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Among other functionalities, with GPyOpt you can design experiments in parallel,
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use cost models and mix different types of variables in your designs. Many users
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already use GpyOpt for research purposes.
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WWW: https://sheffieldml.github.io/GPyOpt/
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