Introduction - If you have any usage issues, please Google them yourself
Canopy is a clustering algorithm to group objects into simple categories, fast, accurate method. Each object with a multi-dimensional feature space of a point to represent. The algorithm uses a fast approximate distance metric and two distance threshold T1> T2 to deal with. Canopy clustering algorithm to quickly identify how many clusters should be chosen, while finding the center of the cluster, which can greatly optimize the efficiency of the K-means clustering algorithm.