makeCustomResampledMeasure {mlr} | R Documentation |
Construct your own resampled performance measure.
Description
Construct your own performance measure, used after resampling. Note that
individual training / test set performance values will be set to NA
, you
only calculate an aggregated value. If you can define a function that makes
sense for every single training / test set, implement your own Measure.
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.
|
|
(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 “”.
|
Value
Measure.
See Also
Other performance:
ConfusionMatrix
,
calculateConfusionMatrix()
,
calculateROCMeasures()
,
estimateRelativeOverfitting()
,
makeCostMeasure()
,
makeMeasure()
,
measures
,
performance()
,
setAggregation()
,
setMeasurePars()
[Package
mlr version 2.19.2
Index]