a week ago - last edited a week ago
A think you use Fuzzy C-means (FCM) from my extension - Information Selection, and in this case proposed by Thomas solution would work limited, because Fuzzy C-means do not return "CentroidClusterMode" (even it use centroids) instead it returns ClusterModel as output. In this case you can have several options
1) you can use Log operator blouse all clustering methods implemented in this extension returns a special logValue which is called CostFunctionValue - in case of FCM it return the final value of the objective function
2) you can not use Cluster Distance Performance but instead you can use Performance IS (Clustering) which takes as input dataset and cluster centers and returns performance equivalent to Cluster Distance Performance.
You can use Performance IS (Clustering) operator for any clustering method which returns centroids, then you just need to deliver to the "pro" input example set with cluster centers.
3) Use other segmentation performance measures
I attach example process which shows the first two solutions