R/performance.rocr.R

In lulcc: Land Use Change Modelling in R

#' Create ROCR performance objects
#'
#' A wrapper function for \code{ROCR::\link[ROCR]{performance}} (Sing et al,
#' 2005) to create \code{performance} objects from a list of \code{prediction}
#' objects.
#'
#' @param prediction.obj a list of \code{ROCR::\link[ROCR]{prediction}} objects 
#' @param measure performance measure to use for the evaluation. See
#'   \code{ROCR::\link[ROCR]{performance}}
#' @param x.measure a second performance measure. See
#'   \code{ROCR::\link[ROCR]{performance}}
#' @param \dots additional arguments to \code{ROCR::\link[ROCR]{performance}}
#'
#' @seealso \code{ROCR::\link[ROCR]{prediction}},
#' \code{ROCR::\link[ROCR]{performance}}
#' @return A list of \code{performance} objects.
#'
#' @export
#' @rdname performance.rocr
#' 
#' @references Sing, T., Sander, O., Beerenwinkel, N., Lengauer, T. (2005).
#' ROCR: visualizing classifier performance in R. Bioinformatics
#' 21(20):3940-3941.

setGeneric("performance", function(prediction.obj, ...)
           standardGeneric("performance"))

#' @rdname performance.rocr
#' @aliases performance,list-method
setMethod("performance", signature(prediction.obj = "list"),
          function(prediction.obj, measure, x.measure="cutoff", ...) {
              perf <- list()
              for (i in 1:length(prediction.obj)) {
                  perf[[i]] <- ROCR::performance(prediction.obj[[i]], measure, x.measure, ...)
              }
              perf
          }
)