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Uncertainty quantification in classification problems: A Bayesian approach for predicting the effects of further test sampling

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Publication date6/12/2019
Host publicationProceedings of MODSIM2019, 23rd International Congress on Modelling and Simulation
EditorsS. Elsawah
Place of PublicationCanberra
PublisherModelling and Simulation Society of Australia and New Zealand (MSSANZ)
Pages193-199
Number of pages7
ISBN (print)9780975840092
<mark>Original language</mark>English

Abstract

The use of machine learning techniques in classification problems has been shown to be useful in many applications. In particular, they have become increasingly popular in land cover mapping applications in the last decade. These maps often play an important role in environmental science applications as they can act as inputs within wider modelling chains and in estimating how the overall prevalence of particular land cover types may be changing.