mlr3_gKRLS: mlr3 integration

In gKRLS: Generalized Kernel Regularized Least Squares

mlr3 integration

Description

This documents LearnerRegrBam and LearnerClassifBam that allow for mgcv::bam to be used in mlr3 without explicitly loading mlr3extralearners. See ml_gKRLS for examples of how to use this and mlr3 for discussion of the "Learner" objects.

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrBam

Methods

Public methods

• LearnerRegrBam$new()

• LearnerRegrBam$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$encapsulate()
• mlr3::Learner$format()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$print()
• mlr3::Learner$reset()
• mlr3::Learner$train()

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Method new()

Creates a new instance of this [R6][R6::R6Class] class.

Usage

LearnerRegrBam$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrBam$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifBam

Methods

Public methods

• LearnerClassifBam$new()

• LearnerClassifBam$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$encapsulate()
• mlr3::Learner$format()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$print()
• mlr3::Learner$reset()
• mlr3::Learner$train()

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Method new()

Creates a new instance of this [R6][R6::R6Class] class.

Usage

LearnerClassifBam$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifBam$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Wood, Simon N and Goude, Yannig and Simon Shaw. 2015. "Generalized Additive Models for Large Data Sets." Journal of the Royal Statistical Society: Series C (Applied Statistics) 64(1):139-155.

gKRLS documentation built on April 4, 2025, 12:37 a.m.