Title :
A Branch and Bound Clustering Algorithm
Author :
Koontz, Warren L.G. ; Narendra, Patrenahalli M. ; Fukunaga, Keinosuke
Author_Institution :
Bell Laboratories
Abstract :
The problem of clustering N objects into M classes may be viewed as a combinatorial optimization algorithm. In the literature on clustering, iterative hill-climbing techniques are used to find a locally optimum classification. In this paper, we develop a clustering algorithm based on the branch and bound method of combinatorial optimization. This algorithm determines the globally optimum classification and is computationally efficient
Keywords :
Branch and bound, clustering, combinatorial optimization, pattern recognition.; Classification algorithms; Clustering algorithms; Costs; Iterative algorithms; Optimization methods; Pattern recognition; Scattering; Branch and bound, clustering, combinatorial optimization, pattern recognition.;
Journal_Title :
Computers, IEEE Transactions on
DOI :
10.1109/T-C.1975.224336
