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This paper proposes a hierarchical clustering algorithm based on information granularity, which regards clustering on sample data as the procedure of granule merging. In the promoted algorithm, firstly each sample is named with an initial class, then for a given granular threshold those pairs of samples, whose distance among them is less than the threshold, will be merged to one class and generate...
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