PyBanshee version (1.0): A Python implementation of the MATLAB toolbox BANSHEE for Non-Parametric Bayesian Networks with updated features

In this paper we discuss PyBanshee, which is a Python-based open-source implementation of the MATLAB toolbox BANSHEE. PyBanshee constitutes the first fully open-source package to quantify, visualize and validate Non-Parametric Bayesian Networks (NPBNs). The architecture of PyBanshee is heavily based...

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Vydáno v:SoftwareX Ročník 21; s. 101279
Hlavní autoři: Koot, Paul, Mendoza-Lugo, Miguel Angel, Paprotny, Dominik, Morales-Nápoles, Oswaldo, Ragno, Elisa, Worm, Daniël T.H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.02.2023
Elsevier
Témata:
BANSHEE
Copulas
Non-Parametric Bayesian Networks
Python library
Non-Parametric Bayesian Networks
Copulas
BANSHEE
Python library
ISSN:2352-7110, 2352-7110
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Shrnutí:In this paper we discuss PyBanshee, which is a Python-based open-source implementation of the MATLAB toolbox BANSHEE. PyBanshee constitutes the first fully open-source package to quantify, visualize and validate Non-Parametric Bayesian Networks (NPBNs). The architecture of PyBanshee is heavily based on its MATLAB predecessor. It presents the full implementation of existing tools and introduces new modules. Specifically, PyBanshee allows for: (i) choosing fully parametric one-dimensional margins, (ii) choosing different sample sizes for the model-validation tests based on the Hellinger distance, (iii) drawing user-defined sample sizes of the NPBN, (iv) sample-based conditioning sampling (similarly to the closed-source proprietary package UNINET by LightTwist Software) and (v) visualizing the comparison between the histograms of the unconditional and conditional marginal distributions. New detailed examples demonstrating new features are provided.
Bibliografie:addendum
ISSN:2352-7110
2352-7110
DOI:10.1016/j.softx.2022.101279