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BIRCH (Balanced Iterative Reducing and Clustering Using Hierarchies)

• Zhang, Ramakrishnan & Livny, SIGMOD’96
• Incrementally construct a CF (Clustering Feature) tree, a hierarchical data structure for multiphase clustering
• Phase 1: scan DB to build an initial in-memory CF tree (a multi-level compression of the data that tries to preserve the inherent clustering structure of the data)
• Phase 2: use an arbitrary clustering algorithm to cluster the leaf nodes of the CF-tree
• Scales linearly: finds a good clustering with a single scan and improves the quality with a few additional scans
• Weakness: handles only numeric data, and sensitive to the order of the data record