Description

Book Synopsis
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.



Table of 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.

Appendix.

Index.

Pattern Classification 2nd Edition with Computer

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    A Hardback by Richard O. Duda

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      Publisher: John Wiley & Sons Inc
      Publication Date: 24/05/2004
      ISBN13: 9780471703501, 978-0471703501
      ISBN10: 0471703508

      Description

      Book Synopsis
      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.



      Table of 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.

      Appendix.

      Index.

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