Hello,
I am using caret package in order to train a K-Nearest Neigbors algorithm. For
this, I am running this code:
Control <- trainControl(method="cv", summaryFunction=twoClassSummary,
classProb=T)
tGrid=data.frame(k=1:100)
trainingInfo <- train(Formula, data=trainData, method = "knn",tuneGrid=tGrid,
trControl=Control, metric = "ROC")
As you can see, I am interested in obtain the AUC parameter of the ROC. This
code works good but returns the testing error (which the algorithm uses for
tuning the k parameter of the model) as the mean of the error of the
CrossValidation folds. I am interested in return, in addition of the testing
error, the trainingerror (the mean across each fold of the error obtained with
the training data). �How can I do it?
Thank you
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