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Visualizations of hierarchical clustering

Consider the following set of five 2D data points, which we seek to cluster hierarchically.

Lecture23ClustersRaw Old Kiwi.jpg

We may visualize the hierarchical clustering in various ways. One is by a Venn diagram, in which we circle the data points which belong to a cluster, then subsequently circle any clusters that belong to a larger cluster in the hierarchy.

Lecture23VennClusters Old Kiwi.jpg

Another way is to use a dendogram. A dendogram represents the clustering as a tree, with clusters that are more closely grouped indicated as siblings "earlier" in the tree. The dendogram also includes a "similarity scale," which indicates the distance between the data points (clusters) which were grouped to form a larger cluster. For the example dataset above (with distances calculated as Euclidian distance), we have the following dendogram:

Lecture23DendogramCluster Old Kiwi.jpg

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