Looking for optimal k in K-Medoids using the Cluster Distance Performance operator

Question

which is supposed to produce the Davies-Bouldin index for k in K-Medoids.https://docs.rapidminer.com/9.1/studio/operators/validation/performance/segmentation/cluster_distance_performance.html

Used the Tutorial to try to duplicate the process. My results in sequence are:

1 Process looking for k produced by the Davies-Bouldin method.

Result Folder view

Result Graph

Result Centroid table

Result Annotations

AutoModel Results k-means-summary. K-medoids is not a model choice.

What am I missing here looking for the Davies-Bouldin method?

Caperez · Accepted Answer

Hi @tonyboy9,

I understand that you miss the Davies-Bouldin Index in Automodel clustering models. You can apply the Cluster Distance Performance Operator to the resulting  model from Automodel.  I hope that can help you.

Best

tonyboy9 · Accepted Answer

Many thanks to ceaperez for suggesting I try the Cluster Distance Performance Operator.
I used the steps in the tutorial.

This was my first clue Davies-Boudin could be found.

I used the tutorial to set up the process in RapidMiner Studio.

After I ran the above process, on Cluster Model I clicked on PerformanceVector.

On this result, Davies-Bouldin is the choice in the left bar.

And here you have it, Davies-Bouldin. It's only a start, now that I understand how to play with the k parameter inside the operator.