Book contents
- Frontmatter
- Contents
- Preface
- Notation
- 1 Introduction and Examples
- 2 Statistical Decision Theory
- 3 Linear Discriminant Analysis
- 4 Flexible Discriminants
- 5 Feed-forward Neural Networks
- 6 Non-parametric Methods
- 7 Tree-structured Classifiers
- 8 Belief Networks
- 9 Unsupervised Methods
- 10 Finding Good Pattern Features
- A Statistical Sidelines
- Glossary
- References
- Author Index
- Subject Index
Author Index
Published online by Cambridge University Press: 05 August 2014
Book contents
- Frontmatter
- Contents
- Preface
- Notation
- 1 Introduction and Examples
- 2 Statistical Decision Theory
- 3 Linear Discriminant Analysis
- 4 Flexible Discriminants
- 5 Feed-forward Neural Networks
- 6 Non-parametric Methods
- 7 Tree-structured Classifiers
- 8 Belief Networks
- 9 Unsupervised Methods
- 10 Finding Good Pattern Features
- A Statistical Sidelines
- Glossary
- References
- Author Index
- Subject Index
Summary
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- Pattern Recognition and Neural Networks , pp. 391 - 398Publisher: Cambridge University PressPrint publication year: 1996