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Clustering methodology for symbolic ...

Billard, L. (1943-)

Clustering methodology for symbolic data /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Clustering methodology for symbolic data /Lynne Billard, Edwin Diday.
Author:	Billard, L.
other author:	Diday, E.,
Published:	Hoboken, NJ :Wiley,2020.
Description:	vii, 340 p. :ill. ;24 cm.
Subject:	Cluster analysis.
ISBN:	9780470713938 :

Clustering methodology for symbolic data /
Billard, L.1943-

Clustering methodology for symbolic data /Lynne Billard, Edwin Diday. - Hoboken, NJ :Wiley,2020. - vii, 340 p. :ill. ;24 cm. - Wiley series in computational statistics. - Wiley series in computational statistics..

Includes bibliographical references and index.

Introduction -- Symbolic data: basics -- Dissimilarity, similarity, and distance measures -- Dissimilarity, similarity, and distance measures: modal data -- General clustering techniques -- Partitioning techniques -- Divisive hierarchical clustering -- Agglomerative hierarchical clustering.

This book presents all of the latest developments in the field of clustering methodology for symbolic data--paying special attention to the classification methodology for multi-valued list, interval-valued and histogram-valued data methodology, along with numerous worked examples. The book also offers an expansive discussion of data management techniques showing how to manage the large complex dataset into more manageable datasets ready for analyses. Filled with examples, tables, figures, and case studies, Clustering Methodology for Symbolic Data begins by offering chapters on data management, distance measures, general clustering techniques, partitioning, divisive clustering, and agglomerative and pyramid clustering. Clustering Methodology for Symbolic Data will appeal to practitioners of symbolic data analysis, such as statisticians and economists within the public sectors. It will also be of interest to postgraduate students of, and researchers within, web mining, text mining and bioengineering.--

ISBN: 9780470713938 :$90

LCCN: 2019011642Subjects--Topical Terms:

182711
Cluster analysis.

LC Class. No.: QA278.55 / .B55 2020

Dewey Class. No.: 519.5/3

Clustering methodology for symbolic data /
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003 OCoLC
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010 $a 2019011642
020 $a 9780470713938 : $c $90
020 $z 9781119010388 (adobe PDF)
020 $z 9781119010395 (ePub)
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050 0 0 $a QA278.55 $b .B55 2020
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100 1 $a Billard, L. $q (Lynne), $d 1943- $3 435208
245 1 0 $a Clustering methodology for symbolic data / $c Lynne Billard, Edwin Diday.
260 $a Hoboken, NJ : $b Wiley, $c 2020.
300 $a vii, 340 p. : $b ill. ; $c 24 cm.
490 1 $a Wiley series in computational statistics
504 $a Includes bibliographical references and index.
505 0 $a Introduction -- Symbolic data: basics -- Dissimilarity, similarity, and distance measures -- Dissimilarity, similarity, and distance measures: modal data -- General clustering techniques -- Partitioning techniques -- Divisive hierarchical clustering -- Agglomerative hierarchical clustering.
520 $a This book presents all of the latest developments in the field of clustering methodology for symbolic data--paying special attention to the classification methodology for multi-valued list, interval-valued and histogram-valued data methodology, along with numerous worked examples. The book also offers an expansive discussion of data management techniques showing how to manage the large complex dataset into more manageable datasets ready for analyses. Filled with examples, tables, figures, and case studies, Clustering Methodology for Symbolic Data begins by offering chapters on data management, distance measures, general clustering techniques, partitioning, divisive clustering, and agglomerative and pyramid clustering. Clustering Methodology for Symbolic Data will appeal to practitioners of symbolic data analysis, such as statisticians and economists within the public sectors. It will also be of interest to postgraduate students of, and researchers within, web mining, text mining and bioengineering.-- $c Provided by publisher.
650 0 $a Cluster analysis. $3 182711
650 0 $a Multivariate analysis. $3 181905
700 1 $a Diday, E., $e author. $3 857870
776 0 8 $i Online version: $a Billard, L. (Lynne), 1943- author. $t Clustering methodology for symbolic data $d Hoboken, NJ : Wiley, 2019 $z 9781119010388 $w (DLC) 2019018340
830 0 $a Wiley series in computational statistics. $3 541778