R: Specify your own aggregation of measures.

makeAggregation {mlr} | R Documentation

## Specify your own aggregation of measures.

### Description

This is an advanced feature of mlr. It gives access to some inner workings so the result might not be compatible with everything!

### Usage

    makeAggregation(id, name = id, properties, fun)

### Arguments

`id` | (`character(1)`) Name of the aggregation method (preferably the same name as the generated function).
`name` | (`character(1)`) Long name of the aggregation method. Default is `id`.
`properties` | (character) Set of aggregation properties. req.train Are prediction or train sets required to calculate the aggregation? req.test Are prediction or test sets required to calculate the aggregation?
`fun` | (`function(task, perf.test, perf.train, measure, group, pred)`) Calculates the aggregated performance. In most cases you will only need the performances `perf.test` and optionally `perf.train` on the test and training data sets. `task` (Task) The task. `perf.test` (numeric) performance results on the test data sets. `perf.train` (numeric) performance results on the training data sets. `measure` (Measure) Performance measure. `group` (factor) Grouping of resampling iterations. This encodes whether specific iterations 'belong together' (e.g. repeated CV). `pred` (Prediction) Prediction object.

### Value

(Aggregation).

### See Also

aggregations, setAggregation

### Examples

    # computes the interquartile range on all performance values
    test.iqr = makeAggregation(
      id = "test.iqr", name = "Test set interquartile range",
      properties = "req.test",
      fun = function(task, perf.test, perf.train, measure, group, pred) IQR(perf.test)
    )

[Package mlr version 2.17.1 Index]