LearnerLm {mlexperiments}

LearnerLm R6 class

Description

This learner is a wrapper around stats::lm() in order to perform a linear regression. There is no implementation for tuning parameters.

Details

Can be used with

• mlexperiments::MLCrossValidation

Implemented methods:

• ⁠$fit⁠ To fit the model.

• ⁠$predict⁠ To predict new data with the model.

Super class

mlexperiments::MLLearnerBase -> LearnerLm

Methods

Public methods

• LearnerLm$new()

• LearnerLm$clone()

Inherited methods

• mlexperiments::MLLearnerBase$bayesian_scoring_function()
• mlexperiments::MLLearnerBase$cross_validation()
• mlexperiments::MLLearnerBase$fit()
• mlexperiments::MLLearnerBase$predict()

Method new()

Create a new LearnerLm object.

Usage

LearnerLm$new()

Details

This learner is a wrapper around stats::lm() in order to perform a linear regression. There is no implementation for tuning parameters, thus the only experiment to use LearnerLm for is MLCrossValidation

Returns

A new LearnerLm R6 object.

Examples

LearnerLm$new()

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerLm$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

stats::lm()

stats::lm()

Examples

LearnerLm$new()


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## Method `LearnerLm$new`
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LearnerLm$new()