A powerful Python package built on top of PyBNesian that provides comprehensive tools for learning and performing inference with Semiparametric Bayesian Network Classifiers.
Designed for researchers and practitioners in machine learning, spbnclassify enables flexible probabilistic classification by combining the interpretability of Bayesian networks with the modeling power of parametric and nonparametric variables.
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Table of Contents
The Semiparametric Bayesian Network Classifier family is a novel framework combining parametric and nonparametric components to achieve an optimal balance between classification performance and computational efficiency.
A research article describing the methodology and experimental results is currently under review. Detailed results showing the average and standard deviation for each model and dataset presented in the article can be found here.
This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.
- Clone the repo
git clone https://github.com/carloslihu/spbnclassify.git
- Install NPM packages
pip install -r requirements.txt
# To execute the experiments and obtain the results
cd src
bash full-grid-search.sh
# To obtain the aggregated results and comparisons
python compare_models.py- Gaussian Bayesian Network Classifiers
- KDE Bayesian Network Classifiers
- Semiparametric Bayesian Network Classifiers
- Discrete Bayesian Network Classifiers
- Make the package pip-installable
- Improve documentation
See the open issues for a full list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt for more information.
Carlos Li Hu - GitHub profile - carloslihu96@gmail.com
Project Link: https://github.com/carloslihu/spbnclassify