DocumentCode
2370322
Title
Fast PNN-based clustering using k-nearest neighbor graph
Author
Fränti, Pasi ; Virmajoki, Olli ; Hautamäki, Ville
Author_Institution
Dept. of Comput. Sci., Joensuu Univ., Finland
fYear
2003
fDate
19-22 Nov. 2003
Firstpage
525
Lastpage
528
Abstract
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) or 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.
Keywords
graph theory; search problems; statistical analysis; vector quantisation; PNN; agglomerative clustering algorithm; k-nearest neighbor graph; pairwise nearest neighbor; search problem; vector quantization; Clustering algorithms; Computer science; Costs; Distortion measurement; Iterative algorithms; Mean square error methods; Nearest neighbor searches; Optimization methods; Tree graphs; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN
0-7695-1978-4
Type
conf
DOI
10.1109/ICDM.2003.1250968
Filename
1250968
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