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cs.LG2021★ 35 cited
Spatial machine-learning model diagnostics: a model-agnostic distance-based approach
Alexander Brenning
While significant progress has been made towards explaining black-box machine-learning (ML) models, there is still a distinct lack of diagnostic tools that elucidate the spatial be…
stat.ML2021
mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R
Patrick Schratz, Marc Becker, Michel Lang +1
Spatial and spatiotemporal machine-learning models require a suitable framework for their model assessment, model selection, and hyperparameter tuning, in order to avoid error esti…
cs.LG2021★ 26 cited
Transforming Feature Space to Interpret Machine Learning Models
Alexander Brenning
Model-agnostic tools for interpreting machine-learning models struggle to summarize the joint effects of strongly dependent features in high-dimensional feature spaces, which play…