Spatial Machine Learning R package SpatialML version 1.8.2 Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Provides a Geographically Weighted Random Forest regression and a routine to find the optimal bandwidth (Georganos and Kalogirou (2022) <doi:10.3390/ijgi11090471>). A lightweight cross-validation helper for tuning the 'mtry' parameter of a random forest and a generator of synthetic spatial test data are also included. The package depends on 'ranger' as its single random-forest back-end. Software Depends: R (>= 4.1.0) Imports: ranger (>= 0.15.1), stats, graphics, utils Suggests: knitr, markdown, testthat (>= 3.0.0) Stamatis Kalogirou <stamatis.science@gmail.com> Comprehensive R Archive Network (CRAN) Stamatis Kalogirou [aut, cre, cph] (ORCID: <https://orcid.org/0000-0003-1949-6248>), Stefanos Georganos [aut] GPL (>= 2) 2026-07-06 application/tgz https://CRAN.R-project.org/package=SpatialML doi:10.32614/CRAN.package.SpatialML en-GB