Hyperparameter tuning and performance assessment of statistical and machine-learning models using spatial data.

This is a research compendium (RC) for the publication "Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data".

The code (including figures, appendices and the manuscript) is packed in pathogen-modeling-3.zip or can be found directly in the Github repository.

• Publication figures: analysis/paper/submission/3/latex-source-files/
• Appendices: analysis/paper/submission/3/

This RC represents a static snapshot at the time of submission. The Github repository will receive changes after the publication was published.

Data sources

• Atlas Climatico: http://opengis.uab.es/wms/iberia/index.htm
• DEM: ftp://ftp.geo.euskadi.eus/lidar/MDE_LIDAR_2016_ETRS89/
• Lithology: http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home
• pH: https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0
• soil: https://www.isric.org/explore/soilgrids

Licenses

All files are shared via the given license with the exception of "soil.tif" which is shared via the ODbL license.