dot-process_input: Unexported function from cvAUC package
In benkeser/predtmle: Small sample estimators of cross-validated prediction metrics

Unexported function from cvAUC package

1 2	.process_input(predictions, labels, label.ordering = NULL, folds = NULL, ids = NULL, confidence = NULL)

`predictions`	A vector, matrix, list, or data frame containing the predictions.
`labels`	A vector, matrix, list, or data frame containing the true class labels. Must have the same dimensions as `predictions`.
`label.ordering`	The default ordering of the classes can be changed by supplying a vector containing the negative and the positive class label (negative label first, positive label second).
`folds`	If specified, this must be a vector of fold ids equal in length to `predictions` and `labels`, or a list of length V (for V-fold cross-validation) of vectors of indexes for the observations contained in each fold. The `folds` argument must only be specified if the `predictions` and `labels` arguments are vectors.
`ids`	Vector of ids
`confidence`	confidence interval level