I am trying to get statistics of prediction for binary classification
problems and for various training models with caret. Below is an example
that illustrates my need:

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library(caret)

# ... Get X and Y for training a binary classification problem. X is input
(2000, 5) Y is output (2000,1) ...

tmp <- createDataPartition(Y, p = 3/4, times = 3, list = TRUE, groups =
min(5, length(Y)))

myCtrl <- trainControl(method = "boot", index = tmp, timingSamps = 2,
classProbs = TRUE, summaryFunction = twoClassSummary)

RFmodel <- train(X,Y,method='rf',trControl=myCtrl,tuneLength=1,
metric="ROC")
SVMmodel <- train(X,Y,method='svmRadial',trControl=myCtrl,tuneLength=3,
metric="ROC")
KNNmodel <- train(X,Y,method='knn',trControl=myCtrl,tuneLength=10,
metric="ROC")
NNmodel <- train(X,Y,method='nnet',trControl=myCtrl,tuneLength=3, trace =
FALSE, metric="ROC")

# resamps reports ROC, Sens, Spec for all models
resamps <- resamples(list(RF = RFmodel, KNN = KNNmodel, NN = NNmodel, SVM =
SVMmodel))

# Prediction:
# ... Assume I have X_pred and Y_pred for evaluating prediction, with
X_pred  (7000, 5) Y_pred (7000,1) ...
testPred <- predict(list(RF = RFmodel, KNN = KNNmodel, NN = NNmodel, SVM =
SVMmodel), Xtst, type="prob")

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How can I get the statistics of prediction (ROC, etc.) from  X_pred and
Y_pred for *all 4 models*?

Thanks!

James

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