export makeAggregation

R/Aggregation.R

@@ -12,9 +12,37 @@
 #' \item{fun [\code{function(task, perf.test, perf.train, measure, group, pred)}]}{Aggregation function.}
 #' }
 #' @name Aggregation
+#' @seealso \code{\link{makeAggregation}}
 #' @rdname Aggregation
 NULL
 
+
+#' @title Specifiy your own aggregation of measures
+#' 
+#' @description 
+#' This is an adavanced feature of mlr. It gives access to some
+#' inner workings so the result might not be compatible with everything! \cr
+#' 
+#' 
+#' @param id [\code{character(1)}]\cr
+#'   Name of the aggregation method. (Preferably the same name as the generated function)
+#' @param fun [\code{function}]\cr
+#'   A function with following signature: \code{function(task, perf.test, perf.train, measure, group, pred)}
+#'   \itemize{
+#'    \item{\bold{task}}: task (\code{\link{SupervisedTask}}) object
+#'    \item{\bold{perf.test}}: numerical vector of \link{performance} results on the test data set
+#'    \item{\bold{perf.train}}. numerical vector of \link{performance} results on the train data set
+#'    \item{\bold{measure}}: \code{\link{Measure}} object.
+#'    \item{\bold{group}}: grouping vector
+#'    \item{\bold{pred}}: \code{\link{Prediction}} object
+#'   }
+#' @seealso \link{aggregations}, \code{\link{setAggregation}}
+#' @return \link{Aggregation} object
+#' @examples
+#' # computes the interquartile range on all performance values
+#' test.iqr = makeAggregation(id="test.iqr", 
+#'   fun = function (task, perf.test, perf.train, measure, group, pred) IQR(perf.test))
+#' @export
 makeAggregation = function(id, fun) {
   checkArg(id, "character", len=1L, na.ok=FALSE)
   structure(list(id=id, fun=fun), class="Aggregation")

R/aggregations.R

@@ -66,6 +66,13 @@ test.sum = makeAggregation(
   fun = function(task, perf.test, perf.train, measure, group, pred) sum(perf.test)
 )
 
+#' @export
+#' @rdname aggregations
+test.range = makeAggregation(
+  id = "test.range",
+  fun = function(task, perf.test, perf.train, measure, group, pred) diff(range(perf.test))
+)
+
 #' @export
 #' @rdname aggregations
 test.sqrt.of.mean = makeAggregation(
@@ -115,6 +122,20 @@ train.sum = makeAggregation(
   fun = function(task, perf.test, perf.train, measure, group, pred) sum(perf.train)
 )
 
+#' @export
+#' @rdname aggregations
+train.range = makeAggregation(
+  id = "train.range",
+  fun = function(task, perf.test, perf.train, measure, group, pred) diff(range(perf.train))
+)
+
+#' @export
+#' @rdname aggregations
+train.sqrt.of.mean = makeAggregation(
+  id = "train.sqrt.of.mean",
+  fun = function(task, perf.test, perf.train, measure, group, pred) sqrt(mean(perf.train))
+)
+
 #' @export
 #' @rdname aggregations
 b632 = makeAggregation(

man/makeAggregation.Rd

@@ -0,0 +1,40 @@
+\name{makeAggregation}
+\alias{makeAggregation}
+\title{Specifiy your own aggregation of measures}
+\usage{
+makeAggregation(id, fun)
+}
+\arguments{
+  \item{id}{[\code{character(1)}]\cr Name of the
+  aggregation method. (Preferably the same name as the
+  generated function)}
+
+  \item{fun}{[\code{function}]\cr A function with following
+  signature: \code{function(task, perf.test, perf.train,
+  measure, group, pred)} \itemize{ \item{\bold{task}}: task
+  (\code{\link{SupervisedTask}}) object
+  \item{\bold{perf.test}}: numerical vector of
+  \link{performance} results on the test data set
+  \item{\bold{perf.train}}. numerical vector of
+  \link{performance} results on the train data set
+  \item{\bold{measure}}: \code{\link{Measure}} object.
+  \item{\bold{group}}: grouping vector \item{\bold{pred}}:
+  \code{\link{Prediction}} object }}
+}
+\value{
+\link{Aggregation} object
+}
+\description{
+This is an adavanced feature of mlr. It gives access to
+some inner workings so the result might not be compatible
+with everything! \cr
+}
+\examples{
+# computes the interquartile range on all performance values
+test.iqr = makeAggregation(id="test.iqr",
+  fun = function (task, perf.test, perf.train, measure, group, pred) IQR(perf.test))
+}
+\seealso{
+\link{aggregations}, \code{\link{setAggregation}}
+}
+