Masahiro Ryo
,
Boyan Angelov
,
Stefano Mammola
,
Jamie M. Kass
,
Blas M. Benito
,
Florian Hartig
… xAI aims at deciphering the behavior of complex statistical or machine learning models (e.g. neural networks, random forests, boosted regression trees), and can produce more transparent and understandable SDM predictions. … As an example, we perform a reproducible SDM analysis in R on the African elephant and showcase some xAI tools such as local interpretable model-agnostic explanation (LIME) to help interpret local-scale behavior of the model. …
IR