Third IEEE International Conference on Data Mining (ICDM'03) Fast PNN-based Clustering Using K-nearest Neighbor Graph Melbourne, Florida November 19-November 22 ISBN: 0-7695-1978-4
Search for nearest neighbor is the main source of computation in most clustering algorithms. We propose the use of nearest neighbor graph for reducing the number of candidates. The number of distance calculations per search can be reduced from O(N) to O(k) where N is the number of clusters, and k is the number of neighbors in the graph. We apply the proposed scheme within agglomerative clustering algorithm known as the PNN algorithm.
Citation:
Pasi Fr?nti, Olli Virmajoki, Ville Hautam?ki, "Fast PNN-based Clustering Using K-nearest Neighbor Graph," icdm, pp.525, Third IEEE International Conference on Data Mining (ICDM'03), 2003 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||