Cluster analysis and mathematical programming
Hansen, Pierre
Jaumard, Brigitte

Data: 1997
Resum: Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homogeneous and/or well separated. As many types of clustering and criteria for homogeneity or separation are of interest, this is a vast field. A survey is given from a mathematical programming viewpoint. Steps of a clustering study, types of clustering and criteria are discussed. Then algorithms for hierarchical, partitioning, sequential, and additive clustering are studied. Emphasis is on solution methods, i. e. , dynamic programming, graph theoretical algorithms, branch-and-bound, cutting planes, column generation and heuristics. .
Drets: Tots els drets reservats.
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Matèria: Cluster analysis ; Hierarchy ; Partition
Publicat a: Mathematical Programming, vol. 79 n. 1-3 (1997) p. 191-215, ISSN 0025-5610

25 p, 1.4 MB
 Accés restringit a la UAB

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