Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels

ISBN-13: 9781108456906 / Angielski / Miękka / 2018 / 363 str.

William W. Hsieh

Opis

A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

Recenzje

'This book is unique because it presents machine learning in the context of environmental science applications. I found it to be a valuable tool to bring myself up to date with the historical and recent developments in the subject of machine learning, and I believe the reader will too. The purchase price is modest. I highly recommend that any student or researcher interested in machine learning methods obtain a copy.' William Burrows, Canadian Meteorological and Oceanographic Society Bulletin

Spis treści

Preface; 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; Appendix A. Sources for data and codes; Appendix B. Lagrange multipliers; Bibliography; Index.