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Multi Variable Probability Calculus Library

Project description

ProbPy is a Python library that aims to simplify calculations with discrete multi variable probabilistic distributions by offering an abstraction over how data is stored and how the operations between distributions are performed.

The library can be used in the implementation of many algorithms such as Bayes Theorem, Bayesian Inference algorithms like Variable Elimination, Gibbs Ask (MCMC), HMMs implementations, Information Theory, etc.

Currently, there are implementation for Bayesian and Markov Networks with some inference algorithms implemented.

For more information check the GitHub page at:

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Files for ProbPy, version 1.1
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