# 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, ...)

## Value

(any). Model of the underlying learner.

## 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.