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Keyword: random forests (RF)

Random forests and stochastic gradient boosting for predicting tree canopy cover: Comparing tuning processes and model performance

Publications Posted on: August 18, 2015
Random forests (RF) and stochastic gradient boosting (SGB), both involving an ensemble of classification and regression trees, are compared for modeling tree canopy cover for the 2011 National Land Cover Database (NLCD). The objectives of this study were twofold. First, sensitivity of RF and SGB to choices in tuning parameters was explored.