Metadata-Version: 2.1
Name: EasyPyKnn
Version: 0.1.0
Summary: An easy educational implementation of the K nearest neighbours algorithm
Author-email: v0ltis <hello@voltis.me>
Project-URL: Homepage, https://github.com/v0ltis/EasyKNN
Project-URL: Bug Tracker, https://github.com/v0ltis/EasyKNN/issues
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Topic :: Education
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Natural Language :: English
Requires-Python: >=3
Description-Content-Type: text/markdown
License-File: LICENSE

# EasyKNN

EasyKNN is a simple implementation of the K-Nearest Neighbors algorithm in Python. It is designed to be easy to use and easy to understand. It is not designed to be fast or efficient, but rather for educational purposes.

## Installation

EasyKNN is available on PyPI:

```bash
pip install EasyPyKnn
```

## Usage

You can import the library with the following code:
```python
from EasyKNN import Value, Dataset, Plan
```

A few examples of how to use the library are available in the [examples](examples) folder.

## Documentation
Currently, the library is not documented. However, the code is commented and should be easy to understand.

A documentation will be available in the future, but not planned for now.

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License
EasyKNN is licensed under the [MIT](LICENSE) license.

## Authors
EasyKNN was created by Barnabé Havard.
