Intelligent Data Analysis | An Introduction

Michael R. Berthold (u. a.)

ISBN 10: 3540430601 / ISBN 13: 9783540430605

Published by Springer, 2003

About this Item

Intelligent Data Analysis | An Introduction | Michael R. Berthold (u. a.) | Buch | xi | Englisch | 2003 | Springer | EAN 9783540430605 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 104091275

Bibliographic Details

• Title: Intelligent Data Analysis | An Introduction
• Publisher: Springer
• Publication Date: 2003
• Language: English
• ISBN 10: 3540430601
• ISBN 13: 9783540430605
• Binding: Buch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 241W x 160H x 38D millimeters 241 millimeters width by 160 millimeters height by 38 millimeters depth
• Weight: 1048 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This monograph is a detailed introductory presentation of 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, 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 approaches and Support Vector Machines. 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 chapter on Visualization and a higher-level overview of the IDA processes, which illustrates the breadth of application of the presented ideas.

From the Back Cover

 

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.