The website is in Maintenance mode. We are in the process of adding more features.
Any new bookmarks, comments, or user profiles made during this time will not be saved.

AIML.com

Machine Learning Resources

How can you choose the optimal value for ‘k’ in K-Means?

Bookmark this question

The most common way to choose k is to run the algorithm over a range of values and then plot the within-cluster sum of squares, or a similar evaluation metric, against the values of k. While the within-cluster sum of squares will monotonically decrease as k gets larger, there is usually a point where an elbow-like pattern appears, indicating that increasing k beyond that point produces diminishing returns. This is analogous to overfitting in supervised learning. In the example elbow plot below, k=4 would be the best choice, since the magnitude of decrease in WSS beyond 4 clusters diminishes compared to that up to 4.

Leave your Comments and Suggestions below:

Please Login or Sign Up to leave a comment

Partner Ad  

Find out all the ways
that you can

Explore Questions by Topics

Partner Ad

Learn Data Science with Travis - your AI-powered tutor | LearnEngine.com