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Branch-and-Bound Applications in Combinatorial Data Analysis

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Cover of 'Branch-and-Bound Applications in Combinatorial Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 An Introduction to Branch-and-Bound Methods for Partitioning
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    Chapter 3 Minimum-Diameter Partitioning
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    Chapter 4 Minimum Within-Cluster Sums of Dissimilarities Partitioning
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    Chapter 5 Minimum Within-Cluster Sums of Squares Partitioning
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    Chapter 6 Multiobjective Partitioning
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    Chapter 7 Introduction to the Branch-and-Bound Paradigm for Seriation
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    Chapter 8 Seriation—Maximization of a Dominance Index
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    Chapter 9 Seriation—Maximization of Gradient Indices
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    Chapter 10 Seriation—Unidimensional Scaling
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    Chapter 11 Seriation—Multiobjective Seriation
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    Chapter 12 Introduction to Branch-and-Bound Methods for Variable Selection
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    Chapter 13 Variable Selection for Cluster Analysis
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    Chapter 14 Variable Selection for Regression Analysis
Attention for Chapter 3: Minimum-Diameter Partitioning
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Chapter title
Minimum-Diameter Partitioning
Chapter number 3
Book title
Branch-and-Bound Applications in Combinatorial Data Analysis
Published by
Springer, New York, NY, January 2005
DOI 10.1007/0-387-28810-4_3
Book ISBNs
978-0-387-25037-3, 978-0-387-28810-9
View on publisher site
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Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Mathematics 1 100%

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