K-Means-Clustering

Description:

This repository provides a simple implementation of the K-Means clustering algorithm in Python. The goal of this implementation is to provide an easy-to-understand and easy-to-use version of the algorithm, suitable for small datasets.

Features:

• Implementation of the K-Means clustering algorithm
• Example code that demonstrates how to use the algorithm on a toy dataset
• Plots of the clustered data and centroids for visualization
• A simple script for testing the algorithm on custom datasets

Code Structure:

• kmeans.py: The main implementation of the K-Means algorithm
• example.py: Example code that demonstrates how to use the algorithm on a toy dataset
• test.py: A simple script for testing the algorithm on custom datasets

Usage:

Clone the repository using

git clone https://github.com/username/kmeans-clustering-python.git

Install the required dependencies using

pip install -r requirements.txt

Run the example code using

python example.py

Customize the code in 'test.py' to use the algorithm on your own datasets.

Results