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Random Forest Regression Models in Ecology: Accounting for Messy Biological Data and Producing Predictions with Uncertainty
4 references·0 citing·18 second hop
Random Forest Regression Models in Ecology: Accounting for Messy Biological Data and Producing Predictions with Uncertainty (2024)Random Forest Regression Models in Ecolog…Three pitfalls to avoid in machine learning (2019)Three pitfalls to avoid in ma…Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2016)Cross‐validation strategies f…On the use of cross-validation for time series predictor evaluation (2012)On the use of cross-validatio…Maximum entropy sampling (1987)Maximum entropy samplingTime Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Another look at measures of forecast accuracy (2006)A note on the validity of cross-validation for evaluating autoregressive time series prediction (2017)Forecasting: theory and practice (2022)On a Measure of the Information Provided by an Experiment (1956)Algorithmic construction of optimal symmetric Latin hypercube designs (2000)Proceedings of the 2002 Winter Simulation Conference (2002)Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)STATISTICS FOR SPATIAL DATA (1992)Statistics for Spatial Data. (1993)Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002)Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data (2019)Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction (2019)A spatio-temporal analysis investigating completeness and inequalities of global urban building data in OpenStreetMap (2023)Data extraction methods for systematic review (semi)automation: A living systematic review (2021)Mind the gap! On the future of AI research (2021)Data extraction methods for systematic review (semi)automation: Update of a living systematic review (2023)
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References

  • 2016Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure3,629 cited
  • 2012On the use of cross-validation for time series predictor evaluation1,324 cited
  • 1987Maximum entropy sampling603 cited
  • 2019Three pitfalls to avoid in machine learning142 cited

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