Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph

Authors:
Pasi Franti;Olli Virmajoki;Ville Hautamaki
Affiliations:
-;-;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2006

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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.