论文信息 - Optimal variable weighting for ultrametric and additive tree clustering

Optimal variable weighting for ultrametric and additive tree clustering

A method is developed which for a given objects by variables data matrix estimates weighted inter-object distances that are optimally suited for either an ultrametric or an additive tree representation. The effectiveness of the method is demonstrated on two synthetic data sets having a known tree structure and on one real data set. In the final section, some possible extensions of the present method are discussed.

G. Soete

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