Interactive Visualization of K-means Clustering algorithm




I found a very nice and interactive visualization of K-means clustering algorithm, so thought of sharing it!

The algorithm is composed of the following steps:

  1. Place K points into the space represented by the objects that are being clustered. These points represent initial group centroids.
  1. Assign each object to the group that has the closest centroid.
  2. When all objects have been assigned, recalculate the positions of the K centroids.
  3. Repeat Steps 2 and 3 until the centroids no longer move. This produces a separation of the objects into groups from which the metric to be minimized can be calculated.

Hope you would like it! :smile:


You can use Silhouette Plot for visualizing the output of K-means. It does not show the intermediate steps though.