Empirical Comparison of Similarities for Agglomerative Hierarchical Clustering
Shusaku Tsumoto, Shoji Hirano, Tomohiro Kimura, Haruko Iwata · 2018
This paper proposes a method for empirical comparison of distances for agglomerative hierarchical clustering based on rough set-based approximation. When a set of target is given, a level of clustering tree where one branch includes all the targets can be traced with the number of elements included. The pair (#clusters of a level, #elements of a cluster) can be viewed as indices-pair for a given clustering tree.