629 citations · 699 across the 5 of their papers we have counts for
5 papers
Web scraping: a promising tool for geographic data acquisition
Alexander Brenning, Sebastian Henn
With much of our lives taking place online, researchers are increasingly turning to information from the World Wide Web to gain insights into geographic patterns and processes. Web…
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…
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…
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…
Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data
Patrick Schratz, Jannes Muenchow, Eugenia Iturritxa +2
Machine-learning algorithms have gained popularity in recent years in the field of ecological modeling due to their promising results in predictive performance of classification pr…