dot-process_input: Unexported function from cvAUC package

In benkeser/nlpred: Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples

Unexported function from cvAUC package

Description

Unexported function from cvAUC package

Usage

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

Arguments

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

benkeser/nlpred documentation built on June 11, 2022, 3:05 a.m.