Difference: Papers20100623115303 (2 vs. 3)

Revision 32010-08-13 - TheresiaFreska

 
META TOPICPARENT name="AI_GEOSTATSPapers"
Title: Support Vector Regression for Automated Robust Spatial Mapping of Natural Radioactivity
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Date:
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Date: 1 July 2005
  Authors: Alexei Pozdnoukhov
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Link: http://publications.epress.monash.edu/doi/pdfplus/10.2104/ag050021
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Link: http://publications.epress.monash.edu/doi/pdfplus/10.2104/ag050021
  Abstract:

This paper presents an application of Support Vector Regression method for the prediction of an environmental variable such as the level of natural radioactivity. The basics of the method are described, and some practical considerations are presented, including the meaning of the method's parameters and their influence on the model. The use of the prior data is discussed. It is shown how to include the information on the variance of the measurements into the model. The use of cross-validation for tuning the parameters of the algorithm is presented. Some ideas for detecting the unusual training samples with SVR are discussed. Generally, the case study illustrates the usefulness of the considered approach for automated spatial mapping tasks in the presence of prior data.

Reference

Applied GIS
Volume 1, No. 2, August 2005
DOI: 10.2104/ag050021

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