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train_pred
2011 May 12
2
Can ROC be used as a metric for optimal model selection for randomForest?
...o 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 function. However if I do the same with randomForest, I get a warning saying that
"In train.default(x = trainPred, y = trainDep, method = "rf", :
The metric "ROC" was not in the result set. Accuracy will be used instead."
I wonder if ROC metric can be used for randomForest? Have I missed something? Very very grateful if anyone can help!
Best regards,
XiaoLiu
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