Analysis of Clustering by Decision Tree

Hi All,

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.

Perhaps in tidymodels? There are some hierarchical clustering examples.

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