https://github.com/tugot17/k-means-algorithm-from-scratch
The K-Means algorithm, written from scratch using the Python programming language
https://github.com/tugot17/k-means-algorithm-from-scratch
from-scratch k-means-clustering k-means-implementation-in-python kmeans-algorithm
Last synced: 7 months ago
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The K-Means algorithm, written from scratch using the Python programming language
- Host: GitHub
- URL: https://github.com/tugot17/k-means-algorithm-from-scratch
- Owner: tugot17
- License: mit
- Created: 2019-09-16T10:09:36.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-11-22T10:44:11.000Z (over 4 years ago)
- Last Synced: 2023-03-05T12:10:13.267Z (over 2 years ago)
- Topics: from-scratch, k-means-clustering, k-means-implementation-in-python, kmeans-algorithm
- Language: Jupyter Notebook
- Size: 38.1 MB
- Stars: 15
- Watchers: 3
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# K-Means-Algorithm-From-Scratch
The K-Means algorithm, written from scratch using the Python programming language. The main jupiter notebook shows how to write k-means from scratch and shows an example application - reducing the number of colors.
## Getting Started
The main file is [K-means.ipynb](K-means.ipynb)
The code itself, without comments, can be found in the [k-means.py](k-means.py) file
## Image
Image used as example for color reduction was downloaded from [here](https://www.nationalgeographic.com/photography/photo-of-the-day/2012/1/elephants-queen-elizabeth-park-sartore/)
### Prerequisites
```
-numpy
-sklearn
-matplotlib
-cv2
```
## Authors
* [tugot17](https://github.com/tugot17)
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details