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Clustering methodology for symbolic data

Author: L Billard; E Diday
Publisher: Hoboken, NJ ; Chichester, West Sussex : John Wiley & Sons, 2020. ©2020
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:

Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical methods do not have the power or flexibility to make sense of  Read more...

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Billard, L. (Lynne), 1943-
Clustering methodology for symbolic data.
Hoboken, NJ : Wiley, 2019
(DLC) 2019011642
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: L Billard; E Diday
ISBN: 9781119010388 1119010381 111901039X 9781119010401 1119010403 9781119010395
OCLC Number: 1098218680
Description: 1 online resource (vii, 340 pages)
Contents: 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.
Responsibility: Lynne Billard, Edwin Diday.

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