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Data Mining: Foundations and Intelligent Paradigms

Volume 2: Statistical, Bayesian, Time Series and other Theoretical Aspects

  • Dawn E. Holmes
  • Lakhmi C. Jain

Part of the Intelligent Systems Reference Library book series (ISRL, volume 24)

Table of contents

  1. Front Matter
  2. Dawn E. Holmes, Jeffrey Tweedale, Lakhmi C. Jain
    Pages 1-7
  3. Eugenio Cesario, Marco Lackovic, Domenico Talia, Paolo Trunfio
    Pages 57-75
  4. Yannick Le Bras, Philippe Lenca, Stéphane Lallich
    Pages 77-98
  5. Boris Kovalerchuk, Florian Delizy, Logan Riggs, Evgenii Vityaev
    Pages 135-156
  6. Arno Knobbe, Ad Feelders, Dennis Leman
    Pages 183-198
  7. Petri Lehtinen, Matti Saarela, Tapio Elomaa
    Pages 199-216
  8. Foto Aftrati, Gautam Das, Aristides Gionis, Heikki Mannila, Taneli Mielikäinen, Panayiotis Tsaparas
    Pages 217-246
  9. Back Matter

About this book

Introduction

Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 2 of this three volume series, we have brought together contributions from some of the most prestigious researchers in theoretical data mining. Each of the chapters is self contained. Statisticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in data mining.

Keywords

Computational Intelligence Data Mining Health Informatics Intelligent Systems

Editors and affiliations

  • Dawn E. Holmes
    • 1
  • Lakhmi C. Jain
    • 2
  1. 1.Department of Statistics andApplied ProbabilityUniversity of California Santa BarbaraUSA
  2. 2.Knowledge-Based EngineeringUniversity of South AustraliaAdelaide Mawson LakesAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-23241-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-23240-4
  • Online ISBN 978-3-642-23241-1
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site