About: Canopy clustering algorithm

The canopy clustering algorithm in computing is an unsupervised clustering algorithm related to the K-means algorithm. It is intended to speed up clustering operations on large data sets, where using another algorithm directly may be impractical because of the size of the data set. The algorithm proceeds as follows: Cheaply partitioning the data into overlapping subsets, called 'canopies' Perform more expensive clustering, but only within these canopies