mlr3_gKRLS {gKRLS} | R Documentation |
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
Inherited methods
Method new()
Creates a new instance of this [R6][R6::R6Class] class.
Usage
LearnerRegrBam$new()
Method clone()
The objects of this class are cloneable with this method.
Usage
LearnerRegrBam$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Super classes
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifBam
Methods
Public methods
Inherited methods
Method new()
Creates a new instance of this [R6][R6::R6Class] class.
Usage
LearnerClassifBam$new()
Method clone()
The objects of this class are cloneable with this method.
Usage
LearnerClassifBam$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.