Canopy clustering algorithm - Wikipedia

The canopy clustering algorithm is an unsupervised pre-clustering algorithm introduced by Andrew McCallum, Kamal Nigam and Lyle Ungar in 2000.[1] It is often used as preprocessing step for the K-means algorithm or the hierarchical clustering algorithm. It is intended to speed up clustering operations on large data sets, where using another algorithm directly may be impractical due to the size of t

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K-means や階層クラスタリングの前処理として使われるクラスタリングアルゴリズム．