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Hierarchical clustering uses linkage criteria to compute inter-cluster similarity.
Second, the 3-D clustering uses multiple (up to ten) conformers per compound.
k-means clustering uses a centroid-based approach to minimize intra-cluster variation (MacQueen 1967).
Unlike transitive closure that uses single-linkage clustering, collective clustering uses an average linkage approach instead.
The hierarchical clustering uses the normalized BoWR of the On cycles for finding the various operational patterns of the chiller.
Given a set of documents, clustering uses a distance based approach to separate documents into groups, by using general methodologies such as partitioning and hierarchical clustering [17].
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Fig. 4 Document clustering using clustering algorithm.
Table 3 Clustering using the Victor Purpura metric.
Bulo and Pelillo [18] describes hypergraph clustering using evolutionary games.
This was computed by hierarchical clustering using Cluster software.
We confirmed the clustering using Kulldorff's spatial scan statistic.
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