… We survey agglomerative hierarchical clustering algorithms and … at hierarchical self-organizing
maps, and mixture models. We review grid-based clustering, focusing on hierarchical …

… dealt with flat clustering that delivers a non-hierarchical partition … clustering technique, we
cover in this chapter another widely used clustering technique: namely, hierarchical clustering…

… We survey agglomerative hierarchical clustering algorithms and … look at hierarchical
self-organizing maps and mixture models. We review grid-based clustering, focusing on hierarchical …

… be used to formulate clustering algorithms. Suitable alternative … for clustering in general
including hierarchical clustering and … of clustering with coverage also of hierarchical clustering …

… methods generate hierarchical clustering solutions that are … clustering algorithms are ideal
for obtaining hierarchical … , but also better performance in terms of cluster quality. Second, we …

… Clustering of multidimensional … such clustering is hierarchical clustering. This method
starts with a set of distinct points, each of which is considered a separate cluster. The two …

… clusters is formed, this technique proceeds sequentially from tighter, less inclusive clusters
through larger more inclusive clusters and is … benueen clusters and the value of the clustering …

… We present a novel algorithm for agglomerative hierarchical clustering based on evaluating
marginal likelihoods of a probabilistic model. This algorithm has several advantages over …

… hierarchical system of such clusters, and a particular type of distance measure. The
correspondence gives rise to two methods of clustering … one method forms clusters that are …

… A major problem in cluster analysis is that there is no universal agreement on what constitutes
a cluster; and, most investigators think that clustering methods depend on the clusters to …