MERRAMax: A machine learning approach to stochastic convergence with a multi-variate dataset
2020
Using a combination of high end computing and machine learning algorithms we developed a system to interrogate climate reanalysis data in a species distribution model. The results show that this system can be used as a tool to identify key variables of interest relevant to a species and to generate a probability map of the distribution of a species of interest. This opens new avenues for statistical inference in regions with sparse observational data.
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