mlr: makeAggregation – R documentation

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makeAggregation

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).

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)
)

mlr

Machine Learning in R

v2.19.0

BSD_2_clause + file LICENSE

Authors

Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Lars Kotthoff [aut], Patrick Schratz [aut, cre] (<https://orcid.org/0000-0003-0748-6624>), Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut] (<https://orcid.org/0000-0001-5324-5966>), Mason Gallo [aut], Jakob Bossek [ctb] (<https://orcid.org/0000-0002-4121-4668>), Erich Studerus [ctb] (<https://orcid.org/0000-0003-4233-0182>), Leonard Judt [ctb], Tobias Kuehn [ctb], Pascal Kerschke [ctb] (<https://orcid.org/0000-0003-2862-1418>), Florian Fendt [ctb], Philipp Probst [ctb] (<https://orcid.org/0000-0001-8402-6790>), Xudong Sun [ctb] (<https://orcid.org/0000-0003-3269-2307>), Janek Thomas [ctb] (<https://orcid.org/0000-0003-4511-6245>), Bruno Vieira [ctb], Laura Beggel [ctb] (<https://orcid.org/0000-0002-8872-8535>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [ctb], Florian Pfisterer [ctb], Stefan Coors [ctb], Steve Bronder [ctb], Alexander Engelhardt [ctb], Christoph Molnar [ctb], Annette Spooner [ctb]

Initial release