標題: A NEW NONITERATIVE APPROACH FOR CLUSTERING
作者: YIN, PY
CHEN, LH
資訊工程學系
Department of Computer Science
關鍵字: CLUSTERING;C-MEANS ALGORITHM;FIXED-RADIUS;MEAN MINIMUM DISTANCE;NOISE CLUSTER
公開日期: 1-Feb-1994
摘要: In this paper, a new non-iterative clustering method is proposed. It consists of two passes. In the first pass, the mean distance from one object to its nearest neighbor is estimated. Based on this distance, those noises far away from objects are extracted and removed. In the second pass, the mean distance from the remaining objects to their nearest neighbors is computed. Based on the distance, all the intrinsic clusters are then found. The proposed method is non-iterative and can automatically determine the number of clusters. Experimental results also show that the partition generated by the proposed method is more reasonable than that of the well-known c-means algorithm in many complicated object distributions.
URI: http://hdl.handle.net/11536/2642
ISSN: 0167-8655
期刊: PATTERN RECOGNITION LETTERS
Volume: 15
Issue: 2
起始頁: 125
結束頁: 133
Appears in Collections:Articles