Nov 6, 2022 · Spatial cross-validation is increasingly used as a strategy to make the cross-validation folds more independent from each other in ecology and ...
Oct 10, 2022 · We propose how to use tailored spatial cross-validation in this context to achieve more realistic assessment of performance and prudent model ...
Spatial cross-validation accounts for potential spatial auto-correlations in the data, providing a more comprehensive assessment of the model's performance ...
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Nov 6, 2022 · Our study aims at formally introducing spatial cross-validation to the machine learning community. We present experiments on data sets from two different ...
We propose a novel cross validation method, SP-CV, for evaluating models. SP-CV split samples by considering both the geographic and feature spaces.
Code and aggregated data of the paper 'Spatial Cross-Validation for Globally Distributed Data' by R. Beigaitė, M. Mechenich, I. Žliobaitė.
Jan 26, 2023 · We propose a novel workflow for spatial predictive mapping that leverages recent developments in this field and combines them in innovative ways.
Jun 7, 2024 · In this chapter, we delve into the topic of spatial cross-validation, a well known method for model assessment and parameter selection.
Aug 7, 2024 · Spatial CV methods are designed for geographical model transferability assessment, i.e. to test the ability of the model to make predictions for ...
Oct 4, 2023 · Geostatistical learning problems are frequently characterized by spatial autocorrelation in the input features and/or the potential for ...