Supplementary Material for the paper "<b>Machine learning algorithms for the evaluation of risk by tick-borne pathogens in Europe.</b>" by Estrada-Peña and de la Fuente (2024).

The files consist in: a compete GIS dataset (GeoPackage format) of hexagonal grids over Europe, with data on climate, landscape, vegetation features, expected distribution of four species of ticks and 162 species of vertebrates.A metadata for the GeoPackage, explaining the contents of each columnMaps of 11 species of vertebrates, as a proof of concept of the predictive abilities of Machine Learning Algorithms using the descriptive variables of the dataset.Scripts written in Orange data mining software (https://orangedatamining.com) to reproduce the demonstrative parts of the modeling.TO NOTE: THIS MATERIAL IS PROTECTED BY PUBLICATION COPYRIGHT. IT CAN BE USED AS FAR AS IT IS CITED.