Machine Learning for Spatial Environmental Data: Theory, Applications, and Software

1st Edition

Mikhail Kanevski, Vadim Timonin, Alexi Pozdnukhov

EPFL Press
Published June 9, 2009
Reference - 400 Pages
ISBN 9780849382376 - CAT# EF8237

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Summary

This book discusses machine learning algorithms, such as artificial neural networks of different architectures, statistical learning theory, and Support Vector Machines used for the classification and mapping of spatially distributed data.  It presents basic geostatistical algorithms as well. The authors describe new trends in machine learning and their application to spatial data. The text also includes real case studies based on environmental and pollution data. It includes a CD-ROM with software that will allow both students and researchers to put the concepts to practice.  

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