Usage
makeCustomResampledMeasure(measure.id, aggregation.id, minimize = TRUE,
properties = character(0L), fun, extra.args = list(), best = NULL,
worst = NULL, measure.name = measure.id,
aggregation.name = aggregation.id, note = "")
Arguments
measure.id
[character(1)]
Short name of measure.
aggregation.id
[character(1)]
Short name of aggregation.
minimize
[logical(1)]
Should the measure be minimized?
Default is TRUE.
properties
[character]
Set of measure properties. For a list of values see Measure.
Default is character(0). fun
[function(task, group, pred, extra.args)]
Calculates performance value from ResamplePrediction object.
For rare cases you can also use the task, the grouping or the extra arguments extra.args.
task [Task]-
The task.
group [factor]-
Grouping of resampling iterations. This encodes whether specific iterations
'belong together' (e.g. repeated CV).
pred [Prediction]-
Prediction object.
extra.args [list]-
See below.
extra.args
[list]
List of extra arguments which will always be passed to fun.
Default is empty list.
best
[numeric(1)]
Best obtainable value for measure.
Default is -Inf or Inf, depending on minimize.
worst
[numeric(1)]
Worst obtainable value for measure.
Default is Inf or -Inf, depending on minimize.
measure.name
[character(1)]
Long name of measure.
Default is measure.id.
aggregation.name
[character(1)]
Long name of the aggregation.
Default is aggregation.id.
note
[character]
Description and additional notes for the measure. Default is “”.