The paper focuses on the problem to find an ultrametric whose distortion is close to optimal. We introduce the Minkowski ultrametric distances of the statistical units obtained by a hierarchical Cluster method (single linkage). Let X be a matrix of quantitative variables observed on n statistical units. We consider the distortion matrix which measures the difference between the initial dissimilarity and the ultrametric approximation. We propose an Algorithm that by means of the Minkowski ultrametrics reaches a minimum approximation. The convergence of the algorithm allows to identify when the ultrametric approximation is at the local minimum. We highlight the validity of the Algorithm by its application to sets of real data.
The progressive single linkage algorithm based on Minkowski ultrametrics / Scippacercola, Sergio. - STAMPA. - unico:(2007), pp. 585-588. (Intervento presentato al convegno Classification and Data Analysis 2007 tenutosi a Macerata nel 12-14 settembre 2007).
The progressive single linkage algorithm based on Minkowski ultrametrics
SCIPPACERCOLA, SERGIO
2007
Abstract
The paper focuses on the problem to find an ultrametric whose distortion is close to optimal. We introduce the Minkowski ultrametric distances of the statistical units obtained by a hierarchical Cluster method (single linkage). Let X be a matrix of quantitative variables observed on n statistical units. We consider the distortion matrix which measures the difference between the initial dissimilarity and the ultrametric approximation. We propose an Algorithm that by means of the Minkowski ultrametrics reaches a minimum approximation. The convergence of the algorithm allows to identify when the ultrametric approximation is at the local minimum. We highlight the validity of the Algorithm by its application to sets of real data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.