Visualize and interact with the clustering algorithm k-means.
Try it at lettier.com/kmeans.
Read more about k-means.
git clone https://github.com/lettier/interactivekmeans.git
cd interactivekmeans
nohup python -m http.server &> /dev/null &
python -mwebbrowser http://localhost:8000
- Lay down data points by clicking the mouse.
- You can also use the
scatter
button located in the controls. - Set your value for
k
andmaxIterations
. - 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