Comparing different methods of agglomerative hierarchical clustering with pairwise constraints

Abstract

Although semi-supervised classification has widely been studied by many researchers, semi-supervised agglomerative hierarchical clustering is not popular. Two methods to introduce pairwise constraint to agglomerative hierarchical clustering have been proposed so far. The first method is to modify distance between two objects that should be in difference clusters by using a kernel function. The second method is to add a penalty term to similarity measure. In addition, difference of linkage methods of agglomerative hierarchical clustering should be compared to observe how the difference affects the resulting clusters. In this paper, we compare different linkage methods with the above two methods for pairwise constraints. Moreover asymmetric similarity measure is considered. Effects of pairwise constraints are shown by simple examples.