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2011 May 12
2
Can ROC be used as a metric for optimal model selection for randomForest?
Dear all, I am using the "caret" Package for predictors selection with a randomForest model. The following is the train function: rfFit<- train(x=trainRatios, y=trainClass, method="rf", importance = TRUE, do.trace = 100, keep.inbag = TRUE, tuneGrid = grid, trControl=bootControl, scale = TRUE, metric = "ROC") I wanted to use ROC as the metric for variable selection. I know that this works with the logit model by making sure that classProbs = TRUE and summaryFunction = twoClassSummary in the trainControl functi...