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Intelligent Data Analysis: An Introduction

Editat de Michael R. Berthold, David J. Hand
en Limba Engleză Hardback – 6 noi 2006
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 stochastic search methods. The book concludes with a chapter on visualization and an advanced overview of IDA processes.
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Specificații

ISBN-13: 9783540430605
ISBN-10: 3540430601
Pagini: 528
Ilustrații: XI, 515 p.
Dimensiuni: 160 x 240 x 38 mm
Greutate: 0.84 kg
Ediția:2nd rev. and ext. ed. 2003. Corr. 2nd printing 2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Descriere

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.

Cuprins

Statistical Concepts.- Statistical Methods.- Bayesian Methods.- Support Vector and Kernel Methods.- Analysis of Time Series.- Rule Induction.- Neural Networks.- Fuzzy Logic.- Stochastic Search Methods.- Visualization.- Systems and Applications.

Recenzii

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)

Textul de pe ultima copertă

 
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.

Caracteristici

An introduction to the diverse areas of modern Data Analysis
Extensive Coverage of interdisciplinary field by leading experts in the field
Twelve introductory chapters, edited to build upon each other
Uniform nomenclature
Includes supplementary material: sn.pub/extras