A new approach to isotonic agglomerative hierarchical clustering
type: Item
instance of: scholarly article
title: A new approach to isotonic agglomerative hierarchical clustering
zbMATH Open document ID: 0777.92026
DOI: 10.1007/BF02616240
author: Werner Vach
author: Paul O. Degens
published in: Journal of Classification
publication date: 1993-02-04T00:00:00Z
review text: A clustering is a type of classification imposed on a finite set of objects. In the paper a new approach to agglomerative hierarchical clustering is presented. The new agglomerative algorithms presented are described by a level statistic to determine the level of joining the clusters and the selection statistic which selects the pairs of clusters to be joined. For traditional agglomerative algorithms, the level statistic and selection statistic are identical. Two examples concerning generalizations of complete linkage and average linkage are illustrated.
Mathematics Subject Classification ID: 91C20
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 110420
zbMATH Keywords: locally optimal ultrametrics
zbMATH Keywords: least squares approximation
zbMATH Keywords: approximation from above
zbMATH Keywords: classification
zbMATH Keywords: agglomerative hierarchical clustering
zbMATH Keywords: new agglomerative algorithms
zbMATH Keywords: level statistic
zbMATH Keywords: selection statistic
zbMATH Keywords: generalizations of complete linkage and average linkage
reviewed by: Ludovit Niepel
MaRDI profile type: Publication
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Wikidata QID: Q58434269
description: scientific article; zbMATH DE number 110420