Density Plug-In Kernel Learner

Calls plugdensity::plugin.density from package plugdensity.

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("dens.plug")
lrn("dens.plug")

Traits

• Packages: plugdensity

• Predict Types: pdf

• Feature Types: integer, numeric

• Properties: missings

References

J. Engel, Eva Herrmann and Theo Gasser (1994). An iterative bandwidth selector for kernel estimation of densities and their derivatives. Journal of Nonparametric Statistics 4, 21–34.

See also

Dictionary of Learners: mlr3::mlr_learners

Author

RaphaelS1

Super classes

mlr3::Learner -> mlr3proba::LearnerDens -> LearnerDensPlugin

Methods

Public methods

• LearnerDensPlugin$new()

• LearnerDensPlugin$clone()

Inherited methods

• 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 class.

Usage

LearnerDensPlugin$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerDensPlugin$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# stop example failing with warning if package not installed
learner = suppressWarnings(mlr3::lrn("dens.plug"))
print(learner)
#> <LearnerDensPlugin:dens.plug>
#> * Model: -
#> * Parameters: list()
#> * Packages: plugdensity
#> * Predict Type: pdf
#> * Feature types: integer, numeric
#> * Properties: missings

# available parameters:
learner$param_set$ids()
#> [1] "na.rm"