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

What is a dendrogram, and how is it used in hierarchical clustering?

Bookmark this question

A dendrogram is a tree-like diagram that visualizes the successive process for how clusters are formed in a hierarchical clustering algorithm. All of the data points are shown on the x-axis, and branches are drawn from the observations to the clusters they are assigned to. The y-axis represents the cluster distance between existing clusters and observations at each step of the process. As hierarchical clustering does not require the user to pre-specify the number of clusters, a common heuristic to decide on a good number of clusters is to horizontally “cut” the dendrogram at a point where it seems the distance between observations joined to clusters is getting too large. A large distance between observations and existing clusters implies that more dissimilar points are being combined into the same cluster. 

In the example drawing below, performing cut 1 would result in 2 clusters, where the first contains observations 1,2,3,4,5, and the second contains observations 6,7,8. Cut 2 would produce 3 clusters, with the first containing observations 1,2,3; the second consisting of observations 4,5; and the third 6,7,8. Finally, Cut 3 would produce 5 clusters,with the first containing observations 1,2; the second observation 3 alone; the third observations 4,5; the fourth observation 6 alone; and the fifth observations 7,8.

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