Direct reading algorithm for hierarchical clustering

DOI10.1016/j.endm.2016.11.006zbMath1404.68041OpenAlexW2559377253MaRDI QIDQ509277

Pedro Contreras, Fionn Murtagh

Publication date: 9 February 2017

Full work available at URL: https://doi.org/10.1016/j.endm.2016.11.006

zbMATH Keywords

hierarchical clusteringanalyticsultrametric topology\(p\)-adic and \(m\)-adic number representationlinear-time computational complexity

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Analysis of algorithms and problem complexity (68Q25) Theory of data (68P99)

Related Items (1)

A survey on feature weighting based K-means algorithms

Cites Work

• Fast, linear time hierarchical clustering using the Baire metric
• Hierarchical trees can be perfectly scaled in one dimension
• Symmetry in data mining and analysis: a unifying view based on hierarchy
• Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding
• Least squares quantization in PCM
• Seriation and matrix reordering methods: An historical overview

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