Dear Community I have constructed a workflow as below. My data contain categorical predictors, natural language and a target. The text miner nodes creates predictors from the text. Three models were trained: a Neural Network, Lasso with cross validation (LARS node) and a Random Forest. The first Random Forest node makes predictor selection. I used the ROC Index in the Model Comparison Node for model selection. The chosen model (Random Forest) was then validated using an independent test set. I would like to publish the results (ROC Index for the test set) but in my field (biomedical research) 95% confidence intervals (CI) are expected/mandatory. As far as I understand, confidence intervals can not be produced by the Model Comparison node. Does anyone know how to calculate a ROC Index 95% CI (for the test set) for for a Random Forest model (or a Lasso model) using SAS Enterprise Miner 14.1 implemented in the workflow above? Thanks. -Andreas
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