標題: FEATURE-PRESERVING CLUSTERING OF 2-D DATA FOR 2-CLASS PROBLEMS USING ANALYTICAL FORMULAS - AN AUTOMATIC AND FAST APPROACH
作者: LIN, JC
TSAI, WH
交大名義發表
資訊工程學系
National Chiao Tung University
Department of Computer Science
關鍵字: 2-CLASS CLUSTERING;CLUSTER REPRESENTATIVES;FEATURE-PRESERVING;ANALYTICAL FORMULAS;DECISION BOUNDARY;AUTOMATIC FAST CLUSTERING;K-MEANS;HIERARCHICAL METHODS
公開日期: 1-May-1994
摘要: We propose in this correspondence a new method to perform two-class clustering of 2-D data in a quick and, automatic way by preserving certain features of the input data. The method is analytical, deterministic, unsupervised, automatic, and noniterative. The computation time is of order n if the data size is n, and hence much faster than any other method which requires the computation of an n-by-n dissimilarity matrix. Furthermore, the proposed method does not have the trouble of guessing initial values. This new approach is thus more suitable for fast automatic hierarchical clustering or any other fields requiring fast automatic two-class clustering of 2-D data. The method can be extended to cluster data in higher dimensional space. A 3-D example is included.
URI: http://dx.doi.org/10.1109/34.291439
http://hdl.handle.net/11536/2524
ISSN: 0162-8828
DOI: 10.1109/34.291439
期刊: IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Volume: 16
Issue: 5
起始頁: 554
結束頁: 560
Appears in Collections:Articles


Files in This Item:

  1. A1994NP14100014.pdf