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Random Forest
Local Knowledge Graph (40 entities)
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Description
Random Forest regression to predict ecosystem drought sensitivity from hydrological and topographic variables. Uses bootstrapped subsampling with multiple regression trees to identify key predictive variables and their importance rankings.
Typical Equipment
- R software
- randomForest package
Output Measurements
- drought sensitivity predictions
- variable importance rankings
- model performance metrics
Papers Using This Protocol (4)
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Model and remote-sensing-guided experimental design and hypothesis generation for monitoring snow-soil–plant interactions
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Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps
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A hybrid data-model approach to map soil thickness in mountain hillslopes
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