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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

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