Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential.

PeerJ · 2018 · PMC6109375 · PMID 30155360

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highly significantno p-value reported

The models for FAPAR were highly significant with R-squared around 90% and RMSE at ± 24 (original values in the range 0–232 where 235 corresponds to FAPAR = 100%) for the most accurate model based on fivefold Leave-Location-Out cross-validation.

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