Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning
  in R   Spatial and spatiotemporal machine-learning models require a suitable
framework for their model assessment, model selection, and hyperparameter
tuning, in order to avoid error estimation bias and over-fitting. This
contribution reviews the state-of-the-art in spatial and spatiotemporal CV, and
introduces the \proglang{R} package mlr3spatiotempcv as an extension package of
the machine-learning framework \textbf{mlr3}. Currently various \proglang{R}
packages implementing different spatiotemporal partitioning strategies exist:
\pkg{blockCV}, \pkg{CAST}, \pkg{kmeans} and \pkg{sperrorest}. The goal of
\pkg{mlr3spatiotempcv} is to gather the available spatiotemporal resampling
methods in \proglang{R} and make them available to users through a simple and
common interface. This is made possible by integrating the package directly
into the \pkg{mlr3} machine-learning framework, which already has support for
generic non-spatiotemporal resampling methods such as random partitioning. One
advantage is the use of a consistent nomenclature in an overarching
machine-learning toolkit instead of a varying package-specific syntax, making
it easier for users to choose from a variety of spatiotemporal resampling
methods. This package avoids giving recommendations which method to use in
practice as this decision depends on the predictive task at hand, the
autocorrelation within the data, and the spatial structure of the sampling
design or geographic objects being studied.

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The categories of this paper are: nlin
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The categories of this paper are: math
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The categories of this paper are: quant-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: funct-an
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The categories of this paper are: gr-qc
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The categories of this paper are: eess
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The categories of this paper are: physics
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The categories of this paper are: adap-org
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The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-alg
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The categories of this paper are: solv-int
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The categories of this paper are: acc-phys
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The categories of this paper are: comp-gas