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Agglomerative Hierarchical Clustering 1. Compute a distance matrix 2. Merge the two closest clusters 3. Update the distance matrix 4. Repeat Step 2 until only one cluster remains

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Distance Between Clusters … Min distance Distance between two closest objects Min < threshold: Single-link Clustering Max distance Distance between two farthest objects Max < threshold: Complete-link Clustering Average distance Average of all pairs of objects from the two clusters

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… Distance Between Clusters Mean distance Increased SSE (Ward’s Method)

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Min Distance Clustering Example... 1 2 5 3 6 4

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... Min Distance Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

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Max Distance Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

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Average Distance Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

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Ward’s Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

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About Hierarchical Clustering Produces a hierarchy of clusters Lack of a global objective function Merging decisions are final Expensive Often used with other clustering algorithms

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Hierarchical Clustering Produces a set of nested clusters organized as a hierarchical tree Can be visualized as a dendrogram – A tree like diagram that.

Hierarchical Clustering Produces a set of nested clusters organized as a hierarchical tree Can be visualized as a dendrogram – A tree like diagram that.

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