ISSN:
1432-1343
Keywords:
Hierarchical clustering
;
Path length trees
;
Mathematical programming
;
Constrained classification methods
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract A mathematical programming algorithm is developed for fitting ultrametric or additive trees to proximity data where external constraints are imposed on the topology of the tree. The two procedures minimize a least squares loss function. The method is illustrated on both synthetic and real data. A constrained ultrametric tree analysis was performed on similarities between 32 subjects based on preferences for ten odors, while a constrained additive tree analysis was carried out on some proximity data between kinship terms. Finally, some extensions of the methodology to other tree fitting procedures are mentioned.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01896984
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