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Intelligent Data Analysis

An Introduction

  • Michael Berthold
  • David J. Hand

Table of contents

  1. Front Matter
    Pages I-IX
  2. David J. Hand
    Pages 1-14
  3. Ad J. Feelders
    Pages 15-66
  4. Paul Taylor
    Pages 67-127
  5. Marco Ramoni, Paola Sebastiani
    Pages 129-166
  6. Elizabeth Bradley
    Pages 167-194
  7. Gerard C. van den Eijkel
    Pages 195-216
  8. Rosaria Silipo
    Pages 217-268
  9. Michael Berthold
    Pages 269-298
  10. Christian Jacob
    Pages 299-350
  11. Xiaohui Liu
    Pages 351-364
  12. Back Matter
    Pages 365-401

About this book

Introduction

This monograph is a detailed introcuctory presentation of the key classes of intelligent data analysis methods. The ten coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues, ranging from the basic concepts of probability, through general notions of inference, to advanced multivariate and time series methods, as well as a detailed discussion of the increasingly important Bayesian approach. The following chapters then concentrate on the area of machine learning and artificial intelligence and provide introductions into the topics of rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a higher level overview of the IDA process and illustrations of the breadth of application of the ideas. The book will become a valuable source of reference for professionals concerned with modern data analysis. Students as well as IT professionals interested in learning about intelligent data analysis will appreciate the book as useful text enhanced by numerous illustrations and examples.

Keywords

Time series artificial intelligence data analysis fuzzy logic intelligence learning machine learning modeling networks neural networks

Editors and affiliations

  • Michael Berthold
    • 1
  • David J. Hand
    • 2
  1. 1.Berkeley Initiative in Soft Computing, Computer Science DivisionUniversity of CaliforniaBerkeleyUSA
  2. 2.Department of StatisticsThe Open UniversityMilton KeynesUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-03969-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 1999
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-662-03971-7
  • Online ISBN 978-3-662-03969-4
  • Buy this book on publisher's site
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