LearnerGlm: LearnerGlm R6 class

In mlexperiments: Machine Learning Experiments

LearnerGlm R6 class

Description

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

Details

Can be used with

• MLCrossValidation

Implemented methods:

• ⁠$fit⁠ To fit the model.

• ⁠$predict⁠ To predict new data with the model.

Super class

mlexperiments::MLLearnerBase -> LearnerGlm

Methods

Public methods

• LearnerGlm$new()

• LearnerGlm$clone()

Inherited methods

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

---

Method new()

Create a new LearnerGlm object.

Usage

LearnerGlm$new()

Details

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

Returns

A new LearnerGlm R6 object.

Examples

LearnerGlm$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerGlm$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

stats::glm()

stats::glm()

Examples

LearnerGlm$new()


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## Method `LearnerGlm$new`
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LearnerGlm$new()

mlexperiments documentation built on April 12, 2025, 1:40 a.m.