Computational experience on four algorithms for the hard clustering problem
- 6 March 1996
- journal article
- research article
- Published by Elsevier in Pattern Recognition Letters
- Vol. 17 (3), 295-308
- https://doi.org/10.1016/0167-8655(95)00122-0
Abstract
No abstract availableKeywords
This publication has 11 references indexed in Scilit:
- A Tabu search approach to the clustering problemPattern Recognition, 1995
- Cluster analysis by the K-means algorithm and simulated annealingChemometrics and Intelligent Laboratory Systems, 1994
- Cluster analysis by simulated annealingComputers & Chemistry, 1994
- A practical application of simulated annealing to clusteringPattern Recognition, 1992
- A simulated annealing algorithm for the clustering problemPattern Recognition, 1991
- Experiments in projection and clustering by simulated annealingPattern Recognition, 1989
- K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local OptimalityIEEE Transactions on Pattern Analysis and Machine Intelligence, 1984
- A Branch and Bound Clustering AlgorithmIEEE Transactions on Computers, 1975
- N‐DIMENSIONAL LOCATION MODELS: AN APPLICATION TO CLUSTER ANALYSISJournal of Regional Science, 1973
- Cluster Analysis and Mathematical ProgrammingJournal of the American Statistical Association, 1971