I am working on validating a cluster analysis. I have read somewhere the approach to cross-validate the cluster analysis. The link of the article is http://jonathantemplin.com/files/clustering/psyc993_03.pdf -
1. Divide data into two subsets: A and B. 2. Apply clustering algorithm to A – get c classes. 3. Each object in B is assigned to “closest” class in A. 4. Apply clustering algorithm to B – get c classes. 5. Compare partitions of B (based on #3 and #4). – If agreement is high, have high confidence in result
Regarding the 5th point, do "partitions" refers to cluster members? How can we calculate agreement between both the partitions? Is it a valid technique to cross-validate the cluster analysis?