mlr3_gKRLS | R Documentation |
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.
mlr3::Learner
-> mlr3::LearnerRegr
-> LearnerRegrBam
new()
Creates a new instance of this [R6][R6::R6Class] class.
LearnerRegrBam$new()
clone()
The objects of this class are cloneable with this method.
LearnerRegrBam$clone(deep = FALSE)
deep
Whether to make a deep clone.
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifBam
new()
Creates a new instance of this [R6][R6::R6Class] class.
LearnerClassifBam$new()
clone()
The objects of this class are cloneable with this method.
LearnerClassifBam$clone(deep = FALSE)
deep
Whether to make a deep clone.
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.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.