Intelligent Data Analysis

An Introduction

  • Michael Berthold
  • David J. Hand

Table of contents

  1. Front Matter
    Pages I-XI
  2. David J. Hand
    Pages 1-15
  3. Ad J. Feelders
    Pages 17-68
  4. Paul Taylor
    Pages 69-129
  5. Marco Ramoni, Paola Sebastiani
    Pages 131-168
  6. Nello Cristianini, John Shawe-Taylor
    Pages 169-197
  7. Elizabeth Bradley
    Pages 199-227
  8. Peter Flach, Nada Lavrač
    Pages 229-267
  9. Rosaria Silipo
    Pages 269-320
  10. Michael R. Berthold
    Pages 321-350
  11. Christian Jacob
    Pages 351-401
  12. Daniel Keim, Matthew Ward
    Pages 403-427
  13. Xiaohui Liu
    Pages 429-443
  14. Back Matter
    Pages 445-514

About this book

Introduction

 

This monograph is a detailed introductory presentation of the key classes of intelligent data analysis (IDA) methods. The 12 coherently written chapters by leading experts provide complete coverage of the core issues.

The previous edition was completely revised and a new chapter on kernel methods and support vector machines and a chapter on visualization techniques were added. The revised chapters from the original edition cover classical statistics issues, ranging from the basic concepts of probability through general notions of inference to advanced multivariate and time-series methods, and provide a detailed discussion of the increasingly important Bayesian approaches. The remaining chapters then concentrate on the area of machine learning and artificial intelligence and provide introductions to 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 processes, illustrating the breadth of application of the presented ideas.

The second edition features an extensive index, which makes this volume also useful as a quick reference on the key techniques in intelligent data analysis.

Keywords

Bayesian analysis Data Mining Intelligent Data Analysis Machine Learning Neuro-Fuzzy Data Analysis Statistical Data Analysis data visualization fuzzy logic inductive logic programming multi-variate Analysis statistical inference statistical learning support vector machine time series analysis artificial intelligence calculus data analysis data mining intelligence kernel learning logic machine learning neural networks Support Vector Machine time series

Editors and affiliations

  • Michael Berthold
    • 1
  • David J. Hand
    • 2
  1. 1.FB Informatik und InformationswissenschaftUniversität KonstanzKonstanzGermany
  2. 2.Department of MathematicsImperial CollegeLondonUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-48625-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-43060-5
  • Online ISBN 978-3-540-48625-1