fix

R/performance_roc.R

@@ -17,15 +17,6 @@
 #' - `Sensitivity`: It is the True Positive Rate, which is the proportion of
 #'   correctly classified "condition 1" observations.
 #'
-#' It returns the area under the curve (AUC) as a percentage, which corresponds
-#' to the probability that a randomly chosen observation of "condition 1" is correctly
-#' classified by the model as having a higher probability of being "condition 1" than
-#' a randomly chosen "condition 2" observation.
-#'
-#' Applying `as.data.frame()` to the output returns a data frame containing the following:
-#' - `Sensitivity` (that actually corresponds to `1 - Specificity`): It is the False Positive Rate.
-#' - `Sensitivity`: It is the True Positive Rate, which is the proportion of correctly classified "condition 1" observations.
-#'
 #' @param x A numeric vector, representing the outcome (0/1), or a model with
 #'   binomial outcome.
 #' @param predictions If `x` is numeric, a numeric vector of same length