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Pattern classification / Richard O. Duda, Peter E. Hart, David G. Stork.

By: Contributor(s): Material type: TextTextPublication details: New York : Wiley, c2001.Edition: 2nd edDescription: xx, 654 p. : ill. ; 27 cmISBN:
  • 0471056693
  • 9780471056690
Subject(s): DDC classification:
  • 006.4   22
Contents:
Bayesian Decision Theory -- Maximum-Likelihood and Bayesian Parameter Estimation -- Nonparametric Techniques -- Linear Discriminant Functions -- Multilayer Neural Networks -- Stochastic Methods -- Nonmetric Methods -- Algorithm-Independent Machine Learning -- Unsupervised Learning and Clustering.
Summary: The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Books Books Main library General Stacks 006.4 / DU.P 2001 (Browse shelf(Opens below)) 1 Available 001661
Books Books Main library General Stacks 006.4 / DU.P 2001 (Browse shelf(Opens below)) 2 Available 001660

"A Wiley-Interscience Publication."

Includes bibliographical references and index.

Bayesian Decision Theory -- Maximum-Likelihood and Bayesian Parameter Estimation -- Nonparametric Techniques -- Linear Discriminant Functions -- Multilayer Neural Networks -- Stochastic Methods -- Nonmetric Methods -- Algorithm-Independent Machine Learning -- Unsupervised Learning and Clustering.

The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

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