Solved – K modes clustering : how to choose the number of clusters

categorical dataclusteringdata miningmachine learning

I am looking for a proper method to choose the number of clusters for K modes. 

I tried to find the optimal number of clusters by maximizing the average silhouette width though. 

In k-modes,  the average silhouette width increases with the increase of the number of clusters with my case.

So i tried to derive the elbow plot and I got the attached graph.

It is quite hard to which point is the location of a bend in this plot.. 

In this case, how can I choose the best number of groups? 

and Can anyone introduce better method that help choose the optimal number of clusters for K-modes? 

Best Answer

The elbow is at 4.

Afterwards, the drop follows the usual behavior of random data and 1/x curves.

Since the elbow is not very prominent, the results likely are not very good, and you need to evaluate other preprocessing and clustering methods if they work better.

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