I wondered if anyone knew of a method in R for somehow combining supervised learning (a decision tree), with unsupervised clustering of categorical data?
For example, suppose I had used partitioning around medoids as my unsupervised clustering method. Is it possible to analyse clustering using a decision tree thereafter?
I found a small example here: Cluster analysis by R under the title of 'analysis of clustering by decision tree'
Would appreciate if someone knew of similar. I found the package treeClust, but found it challenging to implement.