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Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph
November 2006 (vol. 28 no. 11)
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.

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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 and Machine Intelligence, vol. 28, no. 11, pp. 1875-1881, Nov. 2006, doi:10.1109/TPAMI.2006.227
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