SpatialML: Spatial Machine Learning

Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Allows for a geographically weighted random forest regression including a function to find the optical bandwidth.

Version:	0.1.4
Depends:	R (≥ 4.1.0), ranger (≥ 0.13.1), caret
Published:	2022-06-20
Author:	Stamatis Kalogirou [aut, cre], Stefanos Georganos [aut, ctb]
Maintainer:	Stamatis Kalogirou <stamatis at lctools.science>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	http://lctools.science/
NeedsCompilation:	no
CRAN checks:	SpatialML results

Documentation:

Reference manual:

SpatialML.pdf

Downloads:

Package source:	SpatialML_0.1.4.tar.gz
Windows binaries:	r-devel: SpatialML_0.1.4.zip, r-release: SpatialML_0.1.4.zip, r-oldrel: SpatialML_0.1.4.zip
macOS binaries:	r-release (arm64): SpatialML_0.1.4.tgz, r-oldrel (arm64): SpatialML_0.1.4.tgz, r-release (x86_64): SpatialML_0.1.4.tgz, r-oldrel (x86_64): SpatialML_0.1.4.tgz
Old sources:	SpatialML archive

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