Intelligent Data Analysis: An Introduction / Edition 2

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Overview

This second and revised edition contains a detailed introduction to the key classes of intelligent data analysis methods. The twelve 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. The following chapters concentrate on machine learning and artificial intelligence, rule induction methods, neural networks, fuzzy logic, and shastic search methods. The book concludes with a chapter on visualization and an advanced overview of IDA processes.

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Editorial Reviews

From the Publisher
From the reviews of the second edition:

"One excellent feature of the second addition … . This is a particularly nice overview with excellent descriptions and numerous illustrations, most in color, for a wide variety of types of visualizations. " (E. Ziegel, Technometrics, 2005)

"In this second edition … have expanded the coverage of topics and ensured that this remains the key text for surveying the field. The twelve chapters which make up the book provide an academically rigorous and concise to the key methodologies which make up the discipline. … In all this is a comprehensive survey of the field, and will appeal to graduate and post-graduate students, researchers and academics seeking an overview of the theoretical tools available for intelligently analyzing large, complex data sets." (TechBookReport, November, 2003)

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Product Details

  • ISBN-13: 9783540430605
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 2/1/2007
  • Edition description: 2nd rev. and ext. ed. 2003. Corr. 2nd printing 2006
  • Edition number: 2
  • Pages: 515
  • Sales rank: 1,167,130
  • Product dimensions: 6.00 (w) x 9.40 (h) x 1.00 (d)

Table of Contents

1. Introduction; 2. Statistical Concepts; 3. Statistical Methods; 4. Bayesian Methods; 5. Support Vector and Kernel Methods; 6. Analysis of Time Series; 7. Rule Induction; 8. Neural Networks; 9. Fuzzy Logic; 10. Shastic Search Methods; 11 Visualization; 12. Systems and Applications; Appendix A: Information Theory and Decision Tree Induction; Appendix B: Tools; References; Index; Author Addresses.

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