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Random Forest

Subcategory: machine learning
Standard reference: Breiman 2001
Papers: 4 | Mentions: 6

Local Knowledge Graph (40 entities)

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Knowledge graph centered on Random Forest with 40 nodes and 135 connections. Top connected: snow water equivalent, Colorado River, Satellite-derived foresummer drought sensitivity o, environmental variability, mountain hydrology.

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