Book contents
- Frontmatter
- Contents
- Preface
- List of abbreviations
- 1 Basic notions in classical data analysis
- 2 Linear multivariate statistical analysis
- 3 Basic time series analysis
- 4 Feed-forward neural network models
- 5 Nonlinear optimization
- 6 Learning and generalization
- 7 Kernel methods
- 8 Nonlinear classification
- 9 Nonlinear regression
- 10 Nonlinear principal component analysis
- 11 Nonlinear canonical correlation analysis
- 12 Applications in environmental sciences
- Appendices
- References
- Index
Appendices
Published online by Cambridge University Press: 04 May 2010
Book contents
- Frontmatter
- Contents
- Preface
- List of abbreviations
- 1 Basic notions in classical data analysis
- 2 Linear multivariate statistical analysis
- 3 Basic time series analysis
- 4 Feed-forward neural network models
- 5 Nonlinear optimization
- 6 Learning and generalization
- 7 Kernel methods
- 8 Nonlinear classification
- 9 Nonlinear regression
- 10 Nonlinear principal component analysis
- 11 Nonlinear canonical correlation analysis
- 12 Applications in environmental sciences
- Appendices
- References
- Index
Summary
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
- Type
- Chapter
- Information
- Machine Learning Methods in the Environmental SciencesNeural Networks and Kernels, pp. 318 - 321Publisher: Cambridge University PressPrint publication year: 2009