Clustering Methodology for Symbolic Data

Clustering Methodology for Symbolic Data
Author :
Publisher : John Wiley & Sons
Total Pages : 352
Release :
ISBN-10 : 9781119010388
ISBN-13 : 1119010381
Rating : 4/5 (88 Downloads)

Book Synopsis Clustering Methodology for Symbolic Data by : Lynne Billard

Download or read book Clustering Methodology for Symbolic Data written by Lynne Billard and published by John Wiley & Sons. This book was released on 2019-08-12 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers everything readers need to know about clustering methodology for symbolic data—including new methods and headings—while providing a focus on multi-valued list data, interval data and histogram data 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. Provides new classification methodologies for histogram valued data reaching across many fields in data science Demonstrates how to manage a large complex dataset into manageable datasets ready for analysis Features very large contemporary datasets such as multi-valued list data, interval-valued data, and histogram-valued data Considers classification models by dynamical clustering Features a supporting website hosting relevant data sets 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.


Clustering Methodology for Symbolic Data Related Books

Clustering Methodology for Symbolic Data
Language: en
Pages: 352
Authors: Lynne Billard
Categories: Mathematics
Type: BOOK - Published: 2019-08-12 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Covers everything readers need to know about clustering methodology for symbolic data—including new methods and headings—while providing a focus on multi-va
Clustering Methodology for Symbolic Data
Language: en
Pages: 320
Authors: Lynne Billard
Categories: Mathematics
Type: BOOK - Published: 2019-08-20 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Covers everything readers need to know about clustering methodology for symbolic data—including new methods and headings—while providing a focus on multi-va
Advances in Data Science
Language: en
Pages: 232
Authors: Edwin Diday
Categories: Business & Economics
Type: BOOK - Published: 2020-01-09 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to imp
Analysis of Symbolic Data
Language: en
Pages: 444
Authors: Hans-Hermann Bock
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphic
Symbolic Data Analysis
Language: en
Pages: 330
Authors: Lynne Billard
Categories: Mathematics
Type: BOOK - Published: 2012-05-14 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

With the advent of computers, very large datasets have become routine. Standard statistical methods don’t have the power or flexibility to analyse these effic