Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/80865
Title: On post-clustering evaluation and modification
Authors: Ong, S.H. 
Zhao, X.
Keywords: Cluster validity
Clustering
Density
Fuzzy c-means algorithm
Image segmentation
Issue Date: May-2000
Citation: Ong, S.H.,Zhao, X. (2000-05). On post-clustering evaluation and modification. Pattern Recognition Letters 21 (5) : 365-373. ScholarBank@NUS Repository.
Abstract: Unsupervised clustering algorithms sometimes do not lead to meaningful interpretations of the structure in the data. We propose a new approach in which the concept of cluster density is introduced to assess the quality of an algorithmically generated partition and accordingly guide an amelioration process through split-and-merge operations.
Source Title: Pattern Recognition Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/80865
ISSN: 01678655
Appears in Collections:Staff Publications

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