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Clustering methodology for symbolic data

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Clustering methodology for symbolic data

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering methodology for symbolic dataensColorado State University, USAWiley Series in Computational Statistics is comprised of practical guides and cutting edge research books on new deve

lopments in computational statistics. It features quality authors with a strong applications focus. I he texts in the series provide detailed coverage Clustering methodology for symbolic data

of statistical concepts, methods and case studies in areas at the interface of statistics, computing, and numerics. With sound motivation and a wealt

Clustering methodology for symbolic data

h of practical examples, the books show in concrete terms how to select and to use appropriate ranges of statistical computing techniques in particula

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering methodology for symbolic dataonal methods in statistics to fields of bioinformatics, genomics, epidemiology, business, engineering, finance and applied statistics.Clustering Metho

dology for Symbolic DataLynne BillordUniversity of Georgia, USAEdwin DidoyCEREMADE, Université Paris-Dauphine, Université PSL, Paris, FranceWileyThis Clustering methodology for symbolic data

edition first published 2020© 2020 John Wiley & Sons LidAll rights reserved. No pari OÍ this publication may be reproduced, stored in a retrieval syst

Clustering methodology for symbolic data

em, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on h

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering methodology for symbolic dataay to be identified as the authors of this work has been asserted in accordance with law.Registered OfficesJohn Wiley & Sons, Inc., Ill River Street,

Hoboken, NJ 07030, USAJohn Wiley & Sons Ltd, I ho Atrium. Southern Gate, Chichester, West Sussex, POI9 8SQ, UKEditorial Office9600 Garsington Road, Ox Clustering methodology for symbolic data

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Clustering methodology for symbolic data

iley also publishes its books in a variety of electronic formats and by print-on-demand. Some content that appears in standard print versions of this

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering methodology for symbolic datareparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifica

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Clustering methodology for symbolic data

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Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering methodology for symbolic dataerstanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for yo

ur situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have chan Clustering methodology for symbolic data

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Clustering methodology for symbolic data

any other commercial damages, including but not limited to special, incidental, consequential, or other damages.Library of Congress Cataloging-in-Pub

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering methodology for symbolic dataf Georgia), Edwin Diday (CEREMADE, University Paris-Dauphine, University PSL, Paris, France).Description: Hoboken, NJ: Wiley, 2020.1 Includes bibliogr

aphical references and index. IIdentifiers: LCCN 2019011612 (print) I LCCN 2019018310 (ebook) I ISBN9781 119010388 (Adobe PDF) I ISBN 97811 19010395 ( Clustering methodology for symbolic data

ePub) I ISBN 9780470713938 (hardcover)Subjects: I.CSI I: Cluster analysis. I Multivariate analysis.

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

Clustering Methodology for Symbolic DataWiley Series in Computational StatisticsConsulting Editors:Paolo GiudiciUniversity of Pavia, ItalyGeof H. Give

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