Fast exact pairwise-nearest-neighbor algorithm using groups and clusters rejection criteria

Yi Ching Liaw, Jun Feng Lin, Shen Chuan Tai, Jim Z.C. Lai

研究成果: Conference contribution

摘要

Pairwise-nearest-neighbor (PNN) is an effective method of data clustering, which can usually generate good clustering results, but with high computational complexity. In this paper, a new method is presented to reduce the computational complexity of the PNN algorithm through dividing clusters into groups of clusters and using projections of clusters on differential vectors of group pairs to reject impossible groups and clusters in the nearest neighbor finding process of a cluster. Experimental results show that the proposed algorithm can effectively reduce the computing time and number of distance calculations of the PNN algorithm for data sets from real images. It is noted that the proposed method generates the same clustering results as those produced using the PNN algorithm.

原文English
主出版物標題Proceedings of the IASTED International Conference on Signal and Image Processing, SIP 2009
頁面101-104
頁數4
出版狀態Published - 2009 12月 1
事件IASTED International Conference on Signal and Image Processing, SIP 2009 - Honolulu, HI, United States
持續時間: 2009 8月 172009 8月 19

出版系列

名字Proceedings of the IASTED International Conference on Signal and Image Processing, SIP 2009

Other

OtherIASTED International Conference on Signal and Image Processing, SIP 2009
國家/地區United States
城市Honolulu, HI
期間09-08-1709-08-19

All Science Journal Classification (ASJC) codes

  • 訊號處理
  • 資訊系統
  • 軟體
  • 電氣與電子工程

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