R/Measure_custom_resampled.R
makeCustomResampledMeasure.Rd
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.
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 = "" )
measure.id | ( |
---|---|
aggregation.id | ( |
minimize | ( |
properties | (character) |
fun | ( |
extra.args | (list) |
best | ( |
worst | ( |
measure.name | ( |
aggregation.name | ( |
note | (character) |
Other performance:
ConfusionMatrix
,
calculateConfusionMatrix()
,
calculateROCMeasures()
,
estimateRelativeOverfitting()
,
makeCostMeasure()
,
makeMeasure()
,
measures
,
performance()
,
setAggregation()
,
setMeasurePars()