Package: python3-pomegranate (0.13.5-1)

[ Source: python-pomegranate  ]

Fast, flexible and easy to use probabilistic modelling

pomegranate is a package for probabilistic models in Python that is implemented in cython for speed. It's focus is on merging the easy-to-use scikit-learn API with the modularity that comes with probabilistic modeling to allow users to specify complicated models without needing to worry about implementation details. The models are built from the ground up with big data processing in mind and so natively support features like out-of-core learning and parallelism.

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  dep: libc6 (>= 2.17) [arm64, ppc64el]

  dep: libc6 (>= 2.4) [not amd64, arm64, ppc64el]

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• dep: python3-scipy (>= 0.17.0)

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• sug: python-pomegranate-doc

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Download python3-pomegranate

Download for all available architectures

Architecture	Package Size	Installed Size	Files
amd64	2,423.5 kB	41,440.0 kB	[list of files]
arm64	2,253.0 kB	40,650.0 kB	[list of files]
armel	2,200.2 kB	40,340.0 kB	[list of files]
armhf	2,262.8 kB	38,604.0 kB	[list of files]
i386	2,392.0 kB	41,624.0 kB	[list of files]
mips64el	2,105.3 kB	41,337.0 kB	[list of files]
mipsel	2,124.9 kB	40,961.0 kB	[list of files]
ppc64el	2,403.9 kB	43,228.0 kB	[list of files]
s390x	2,169.8 kB	41,270.0 kB	[list of files]