Hierarchical clustering for large data sets

Abstract

This chapter provides a tutorial overview of hierarchical clustering. Several data visualization methods based on hierarchical clustering are demonstrated and the scaling of hierarchical clustering in time and memory is discussed. A new method for speeding up hierarchical clustering with cluster seeding is introduced, and this method is compared with a traditional agglomerative hierarchical, average link clustering algorithm using several internal and external cluster validation indices. A benchmark study compares the cluster performance of both approaches using a wide variety of real-world and artificial benchmark data sets. © 2013 Springer-Verlag Berlin Heidelberg.