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: https://github.com/petermlm/ProbPy.
Release history Release notifications
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size ProbPy-1.1.tar.gz (15.9 kB) | File type Source | Python version None | Upload date | Hashes View hashes |
