mlr: trainLearner – R documentation

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trainLearner

Train an R learner.

Description

Mainly for internal use. Trains a wrapped learner on a given training set. You have to implement this method if you want to add another learner to this package.

Usage

trainLearner(.learner, .task, .subset, .weights = NULL, ...)

Arguments

`.learner`	(RLearner) Wrapped learner.
`.task`	(Task) Task to train learner on.
`.subset`	(integer) Subset of cases for training set, index the task with this. You probably want to use getTaskData for this purpose.
`.weights`	(numeric) Weights for each observation.
`...`	(any) Additional (hyper)parameters, which need to be passed to the underlying train function.

Details

Your implementation must adhere to the following: The model must be fitted on the subset of .task given by .subset. All parameters in ... must be passed to the underlying training function.

Value

(any). Model of the underlying learner.

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