Combinatorial data analysis. Optimization by dynamic programming
type: Item
instance of: scholarly article
zbMATH Open document ID: 0999.90047
DOI: 10.1137/1.9780898718553
author: Lawrence Hubert
author: Phipps Arabie
author: Jacqueline Meulman
publication date: 2001-07-03T00:00:00Z
Mathematics Subject Classification ID: 90C39
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62-02
Mathematics Subject Classification ID: 92-02
Mathematics Subject Classification ID: 90C27
Mathematics Subject Classification ID: 62P15
zbMATH DE Number: 1614056
zbMATH Keywords: combinatorial data analysis
zbMATH Keywords: cluster analysis
zbMATH Keywords: object sequencing
zbMATH Keywords: seriation
zbMATH Keywords: dynamic programming
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1137/1.9780898718553
OpenAlex ID: W4229588005
title: Combinatorial data analysis. Optimization by dynamic programming
published in: SIAM Monographs on Discrete Mathematics and Applications
review text: The book discusses the application of dynamic programming type algorithms to problems in combinatorial data analysis. The flexibility of the dynamic programming method is highlighted on a variety of different problems with an emphasis on cluster analysis and object sequencing and seriation. Moreover, in the clustering and sequencing context, the general dynamic programming approach is modified to a heuristic procedure to efficiently handle large data sets. NEWLINENEWLINENEWLINEAn appendix is included that can be used as a users manual describing the operation of nineteen programs available as freeware on one of the authors webpage. The programs are related to the individual algorithms described in the preceding chapters and applicable, for example, for object partitioning, hierarchical clustering, object sequencing and seriation, and the construction of ordered partitions.
reviewed by: Kathrin Klamroth
description: scientific article; zbMATH DE number 1614056