Intelligent Data Analysis: An Introduction

Berthold, Michael

ISBN 10: 3540658084 / ISBN 13: 9783540658085

Verlag: Springer, 1999

Beschreibung

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Bestandsnummer des Verkäufers Z1-B-017-01952

Bibliografische Details

• Titel: Intelligent Data Analysis: An Introduction
• Verlag: Springer
• Erscheinungsjahr: 1999
• Sprache: Englisch
• ISBN-10: 3540658084
• ISBN-13: 9783540658085
• Einband: Hardcover
• Zustand: Good

Über diesen Titel

Inhaltsangabe

This monograph is a detailed introductory 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 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 a useful text enhanced by numerous illustrations and examples.

Reseña del editor

This monograph is a detailed introductory 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.