Metadata-Version: 2.1
Name: bnclassify
Version: 1.0.0
Summary: Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Home-page: https://github.com/erdogant/bnlearn
Author: Erdogan Taskesen
Author-email: erdogant@gmail.com
License: UNKNOWN
Download-URL: https://github.com/erdogant/bnclassify/archive/1.0.0.tar.gz
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
License-File: LICENSE

# bnclassify - Probability density fitting.

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### 

``bnlearn`` is Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods. This work is inspired by the R package (bnlearn.com) that has been very usefull to me for many years. Although there are very good Python packages for probabilistic graphical models, it still can remain difficult (and somethimes unnecessarily) to (re)build certain pipelines. Bnlearn for python (this package) is build on the <a href="https://github.com/pgmpy/pgmpy">pgmpy</a> package and contains the most-wanted pipelines. Navigate to [API documentations](https://erdogant.github.io/bnlearn/) for more detailed information.

**Star this repo if you like it! ⭐️**

## 


### Blog/Documentation

* [**Step-by-step guide for structure learning!**](https://towardsdatascience.com/a-step-by-step-guide-in-detecting-causal-relationships-using-bayesian-structure-learning-in-python-c20c6b31cee5)
* [**Step-by-step guide for knowledge-driven models!**](https://link.medium.com/LBp2eW8qNjb)
* [**bnlearn documentation pages (Sphinx)**](https://erdogant.github.io/bnlearn/)


* ``bnclassify`` is Python package that originates from ``bnlearn`` library.
* More information can be found [at the bnlearn library](https://github.com/erdogant/bnlearn)

### Maintainers
* Erdogan Taskesen, github: [erdogant](https://github.com/erdogant)


### Licence
See [LICENSE](LICENSE) for details.


