print.trainDI

show.trainDI

Generic print function for objects of class <code>trainDI</code>.

Supporting functionality to run 'caret' with spatial or spatial-temporal data.
'caret' is a frequently used package for model training and prediction using machine learning.
CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'.
It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate
the performance of spatial prediction models and allows for spatial variable selection to selects
suitable predictor variables in view to their contribution to the spatial model performance.
CAST further includes functionality to estimate the (spatial) area of applicability of prediction models.
Methods are described in
Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>;
Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>;
Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>;
Milà et al. (2022) <doi:10.1111/2041-210X.13851>;
Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>;
Linnenbrink et al. (2024) <doi:10.5194/gmd-17-5897-2024>;
Schumacher et al. (2025) <doi:10.5194/gmd-18-10185-2025>.
The package is described in detail in Meyer et al. (2026) <doi:10.1007/978-3-031-99665-8_11>.

Hanna Meyer

CAST

'caret' Applications for Spatial-Temporal Models

Carles Milà

Marvin Ludwig

Jan Linnenbrink

Fabian Schumacher

Philipp Otto

Chris Reudenbach

Thomas Nauss

Edzer Pebesma

Jakub Nowosad

Darius Görgen

print.trainDI function

<dl><dt>x</dt>
<dd>trainDI object</dd>
<dt>...</dt>
<dd>other params</dd></dl>

Arguments

Print trainDI objects — print.trainDI

<dl>

<dt>x</dt>
<dd>trainDI object</dd>


<dt>...</dt>
<dd>other params</dd>

</dl>

Print trainDI objects

print.trainDI: Print trainDI objects

Description

Usage

Arguments