Jakub Nowosad
I am a computational geographer working at the intersection between geocomputation and the environmental sciences. My research is focused on developing and applying spatial methods to broaden our understanding of processes and patterns in the environment. Vital part of my work is to create, collaborate, and improve geocomputational software. I am an active member of the R-spatial community and a co-author of the Geocomputation with R book.
Beitrag
Machine learning for spatial problems faces unique challenges, notably spatial dependence. Effective modeling requires integrating spatial information and proper validation methods to preserve spatial structure. This poster will overview spatial machine learning packages in R, focusing on tools for feature engineering, validation, and interpretation. It will also serve as a guide for comparing these tools and critically assessing their strengths and limitations.