Generally this base learner class should not be instantiated. Intended to be an abstract class, although abstract classes are not explicitly supported by R6. All learners support the methods and fields documented below. For more information on a particular learner, see its help file.

make_learner(learner_class, ...)

## Arguments

learner_class The learner class to instantiate. Parameters with which to instantiate the learner. See Parameters section below.

R6Class object.

## Value

Learner object with methods for training and prediction

## Common Parameters

Individual learners have their own sets of parameters. Below is a list of shared parameters, implemented by Lrnr_base, and shared by all learners.

covariates

A character vector of covariates. The learner will use this to subset the covariates for any specified task

outcome_type

A variable_type object used to control the outcome_type used by the learner. Overrides the task outcome_type if specified

...

All other parameters should be handled by the invidual learner classes. See the documentation for the learner class you're instantiating

## User Methods

Trains learner to a task using delayed. Returns a fit object

Trains learner to a task. Returns a fit object

• trained_sublearners: Any sublearners previous trained. Almost always NULL

Generates predictions using delayed. Returns a prediction vector or matrix.

Generates predictions. Returns a prediction vector or matrix.

Generates a chained task using delayed

## Fields

is_trained

TRUE if this is a learner fit, not an untrained learner

fit_object

The internal fit object

name

The learner name

learner_uuid

A unique identifier of this learner, but common to all fits of this learner

fit_uuid

A unique identifier of this learner fit. NULL if this is an untrained learner

params

A list of learner parameters, as specified on construction

The task used for training. NULL if this is an untrained learner

training_outcome_type

The outcome_type of the task used for training. NULL if this is an untrained learner

properties

The properties supported by this learner

coefficients

Fit coefficients, if this learner has coefficients. NULL otherwise, or if this is an untrained learner

## Internal Methods

These methods are primiarily for internal use only. They're not recommended for public consumption.

Returns a task with covariates subsetted using the covariates parameter.

Mediates between the task outcome_type and parameter outcome_type. If a parameter outcome_type was specified, returns that. Otherwise, returns the task$outcome_type. • task: The task for which to determine the outcome_type train_sublearners(task) Trains sublearners to a task using delayed. Returns a delayed sublearner fit. • task: The task to use for training set_train(fit_object, training_task) Converts a learner to a learner fit. • fit_object: The fit object generated by a call to private$.train