An easy educational implementation of the K nearest neighbors algorithm
Project description
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:
pip install EasyPyKnn
Usage
You can import the library with the following code:
from EasyKNN import Value, Dataset, Plan
A few examples of how to use the library are available in the 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.
Authors
EasyKNN was created by Barnabé Havard.
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