R: Construct your own resampled performance measure.

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.
`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 “”.

### Value

Measure.

### See Also

Other performance: `ConfusionMatrix`, `calculateConfusionMatrix`, `calculateROCMeasures`, `estimateRelativeOverfitting`, `makeCostMeasure`, `makeMeasure`, `measures`, `performance`, `setAggregation`, `setMeasurePars`

[Package mlr version 2.15.0 Index]