metta-ul: Clustering Algorithms in MeTTa

Overview

metta-ul is a basic implementation of clustering algorithms in the MeTTa language. It includes implementations of:

• K-Means
• Gaussian Mixture Models (GMM)
• Spectral Clustering
• Hierarchical Clustering

This project is packaged as a Python module and includes a Dockerized environment for running tests using pytest.

Authors

• Ramin Barati - me@rbarati.com
• Amirhossein Nourani Zadeh - amirhossein.nouranizadeh@gmail.com
• Farhoud - farhoud.m7@gmail.com

Requirements

• Python 3.7 or later
• hyperon
• numpy
• pandas

Installation

Using pip

pip install metta-ul

Running Tests

First, install PyTest:

pip install pytest

Then, run the tests using:

pytest .

Contributing

1. Fork the repository
2. Create a new branch (feature-branch)
3. Commit changes and push to your branch
4. Submit a pull request

License

This project is licensed under the MIT License.