Context: We are two students intending to write a thesis on reverse engineering namespaces using hierarchical agglomerative clustering algorithms. We have a variation of linking methods and other tweaks to the algorithm we want to try out. We will run the algorithm on popular GitHub repositories and compare the created clusters with the originally existent namespaces. Our work will closely follow the works of this paper. In the paper the authors mentions the use of the “precision recall metric” to measure the accuracy of the clustering algorithm. However looking more closely on the metric and its origin, it seems to be dedicated to flat (non-hierarchical) clusters.
Question: Is there a way to use the precision recall metric to measure the accuracy of a hierarchy of recovered clusters? If not, what other options exists?
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