The Community for Technology Leaders
RSS Icon
Issue No.11 - November (2006 vol.28)
pp: 1875-1881
We propose a fast agglomerative clustering method using an approximate nearest neighbor graph for reducing the number of distance calculations. The time complexity of the algorithm is improved from {\rm O}(\tau N^2) to {\rm O}(\tau N \log N) at the cost of a slight increase in distortion; here, \tau denotes the number of nearest neighbor updates required at each iteration. According to the experiments, a relatively small neighborhood size is sufficient to maintain the quality close to that of the full search.
Clustering, agglomeration, nearest neighbor, vector quantization, PNN.
Pasi Fr?nti, Olli Virmajoki, Ville Hautam?ki, "Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.28, no. 11, pp. 1875-1881, November 2006, doi:10.1109/TPAMI.2006.227
31 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool