frosty-dag

Name	frosty-dag JSON
Version	0.0.2 JSON
	download
home_page	https://github.com/joshuaybang/frosty-dag
Summary	Implementation of the FROSTY algorithm
upload_time	2023-06-16 01:52:23
maintainer
docs_url	None
author	Joshua Bang
requires_python	>=3.6, <3.10
license
keywords	bayesian network structure learning
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # FROSTY

Python Package for the FROSTY algorithm by Joshua Bang and Sang-Yun Oh

Bang, J., Oh, S.-Y. (2023). FROSTY: A High-Dimensional Scale-Free Bayesian Network Learning Method. Journal of Data Science. \[[JDS](https://jds-online.org/journal/JDS/article/1329/info)\]

## Installation

Installation of `scikit-sparse` depends on `suite-sparse` library, which can be installed via:
```bash
# mac
brew install suite-sparse

# debian
sudo apt-get install libsuitesparse-dev
```

Then install FROSTY from PyPI:
```bash
pip install frosty-dag
```

## Example (scale-free graph, p=50, n=1000)

 - True and estimated graphs

![estimation](https://github.com/joshuaybang/frosty/raw/main/examples/images/frosty-estimation.png)

 - Confusion matrix

![confusion matrix](https://github.com/joshuaybang/frosty/raw/main/examples/images/confusion-matrix.png)


            

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