MACHINE LEARNING IN SPECIES DISTRIBUTION MODELING

Catalog description

Explores machine learning (ML) topics for building and evaluating species distribution models (SDMs). Examines ML approaches such as tree-based methods, maximum entropy methods, and cross-validation through reading and discussion of current literature as well as hands-on exercises in the R programming language. Culminates in student projects to apply the material.