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Package: python3-pomegranate (0.13.5-2build1)

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 (>= 2.14) [amd64]
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    also a virtual package provided by libc6-udeb
    dep: libc6 (>= 2.17) [arm64, ppc64el]
    dep: libc6 (>= 2.4) [armhf]
  • dep: python3
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    dep: python3 (<< 3.11)
    dep: python3 (>= 3.10~)
  • dep: python3-joblib
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  • dep: python3-networkx
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  • dep: python3-numpy
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  • dep: python3-scipy
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  • dep: python3-yaml
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Download python3-pomegranate

Download for all available architectures
Architecture Package Size Installed Size Files
amd64 2,400.6 kB39646 kB [list of files]
arm64 2,352.6 kB38836 kB [list of files]
armhf 2,319.0 kB36760 kB [list of files]
ppc64el 2,758.3 kB43115 kB [list of files]