Machine Learning for Spatial Environmental Data

Machine Learning for Spatial Environmental Data

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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.The distribution of the vector Z conditional on Zi =zi (i= 1, 2, ..., M) can be factorised in the form Pr{zM+1a‰c ZM+1 ... This procedure of decomposition of a joint p.d.f into the product of conditional p.d.f is very general and can be used for spatialanbsp;...


Title:Machine Learning for Spatial Environmental Data
Author: Mikhail Kanevski, Vadim Timonin, Alexi Pozdnukhov
Publisher:CRC Press - 2009-06-09
ISBN-13:

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