Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph.

Pasi Fränti, Olli Virmajoki, Ville Hautamäki

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 O(tauN <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) to O(tauN log N) at the cost of a slight increase in distortion; here, tau denotes the lumber 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