A dissimilarity-adaptive cross-validation method for evaluating geospatial machine learning predictions with clustered samples
Spatially clustered samples are prevalent in geospatial machine learning (ML) predictions, especially in ecological mapping. Since densely sampled regions in the prediction area are overrepresented, leading to dissimilarities in the data distribution between samples and predictions and thus posing a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Ecological Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954125002961 |
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