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Issue No.11 - November (2006 vol.28)
pp: 1875-1881
ABSTRACT
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.
INDEX TERMS
Clustering, agglomeration, nearest neighbor, vector quantization, PNN.
CITATION
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
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