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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. (C) 2000 Published by Elsevier Science B.V. All rights reserved.
Keyword:
clustering
density
cluster validity
image segmentation
fuzzy c-means algorithm
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3.3
论文数:
8.0K
被引数:
1.6W
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