Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/lettier/interactivekmeans

Interactive HTML canvas based implementation of k-means.
https://github.com/lettier/interactivekmeans

ai cluster cluster-analysis clustering clustering-algorithm clustering-evaluation clustering-methods data-science interactive-kmeans kmeans kmeans-algorithm kmeans-clustering machine-learning machine-learning-algorithms scikit-learn

Last synced: 3 months ago
JSON representation

Interactive HTML canvas based implementation of k-means.

Awesome Lists containing this project

README

        

![Interactive K-means](preview.gif)

# Interactive K-means

Visualize and interact with the clustering algorithm k-means.
Try it at [lettier.com/kmeans](http://www.lettier.com/kmeans/).
Read more about [k-means](https://lettier.github.io/posts/2016-04-24-k-means-from-scratch.html).

## Download & Run

```bash
git clone https://github.com/lettier/interactivekmeans.git
cd interactivekmeans
nohup python -m http.server &> /dev/null &
python -mwebbrowser http://localhost:8000
```

## Directions

- Lay down data points by clicking the mouse.
- You can also use the `scatter` button located in the controls.
- Set your value for `k` and `maxIterations`.
- Press `runKMeans` to cluster the on-screen data points.
- Remove data points by clicking on them.
- Use the silhouette coefficient to find the optimal `k`.

(C) 2015 David Lettier.
[lettier.com](https://www.lettier.com/)