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
7 - Kernel methods
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
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- Machine Learning Methods in the Environmental SciencesNeural Networks and Kernels, pp. 157 - 169Publisher: Cambridge University PressPrint publication year: 2009
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