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A Nonparametric Algorithm for Detecting Clusters Using Hierarchical Structure

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2 Author(s)
Mizoguchi, Riichiro ; MEMBER, IEEE, Institute of Scientific and Industrial Research, Osaka University, Suita, Osaka, Japan. ; Shimura, Masamichi

The present paper discusses a nonparametric algorithm for detecting clusters. In the algorithm a positive value called potential is associated with each datum based on dissimilarities. By defining subordination relations among data, hierarchical structure is introduced into the data set. As a result of the introduction of hierarchical structure, the data set is divided into some subsets called subclusters. A procedure for constructing clusters from the subclusters is also considered. The proposed algorithm can be applied to a very wide range of data set and has great ability to detect clusters, which is verified by computer simulation.

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-2 ,  Issue: 4 )