Statistical Learning of Complex Data
This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big
- PDF / 4,713,347 Bytes
- 200 Pages / 439.42 x 666.14 pts Page_size
- 28 Downloads / 225 Views
Francesca Greselin Laura Deldossi Luca Bagnato Maurizio Vichi Editors
Statistical Learning of Complex Data
Studies in Classification, Data Analysis, and Knowledge Organization
Managing Editors
Editorial Board Members
Wolfgang Gaul, Karlsruhe, Germany Maurizio Vichi, Rome, Italy Claus Weihs, Dortmund, Germany
Daniel Baier, Bayreuth, Germany Frank Critchley, Milton Keynes, UK Reinhold Decker, Bielefeld, Germany Edwin Diday, Paris, France Michael Greenacre, Barcelona, Spain Carlo Natale Lauro, Naples, Italy Jacqueline Meulman, Leiden, The Netherlands Paola Monari, Bologna, Italy Shizuhiko Nishisato, Toronto, Canada Noboru Ohsumi, Tokyo, Japan Otto Opitz, Augsburg, Germany Gunter Ritter, Passau, Germany Martin Schader, Mannheim, Germany
More information about this series at http://www.springer.com/series/1564
Francesca Greselin • Laura Deldossi • Luca Bagnato • Maurizio Vichi Editors
Statistical Learning of Complex Data
123
Editors Francesca Greselin Department of Statistics and Quantitative Methods University of Milano-Bicocca Milan, Italy Luca Bagnato Department of Economic and Social Sciences Università Cattolica del Sacro Cuore Piacenza, Italy
Laura Deldossi Department of Statistical Sciences Università Cattolica del Sacro Cuore Milan, Italy
Maurizio Vichi Department of Statistical Sciences Sapienza University of Rome Rome, Italy
ISSN 1431-8814 ISSN 2198-3321 (electronic) Studies in Classification, Data Analysis, and Knowledge Organization ISBN 978-3-030-21139-4 ISBN 978-3-030-21140-0 (eBook) https://doi.org/10.1007/978-3-030-21140-0 Mathematics Subject Classification (2010): 62-06, 62-07, 62Fxx, 62Gxx, 62Hxx, 62Jxx, 62Kxx © Springer Nature Switzerland AG 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbes
Data Loading...
