This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Nonparametric Algorithm for Detecting Clusters Using Hierarchical Structure
April 1980 (vol. 2 no. 4)
pp. 292-300
Riichiro Mizoguchi, MEMBER, IEEE, Institute of Scientific and Industrial Research, Osaka University, Suita, Osaka, Japan.
Masamichi Shimura, MEMBER, IEEE, Department of Computer Science, Tokyo Institute of Technology, Tokyo, Japan.
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.
Citation:
Riichiro Mizoguchi, Masamichi Shimura, "A Nonparametric Algorithm for Detecting Clusters Using Hierarchical Structure," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, no. 4, pp. 292-300, April 1980, doi:10.1109/TPAMI.1980.4767028
Usage of this product signifies your acceptance of the Terms of Use.