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Kernel density estimation with global bandwidth selection via "plug-in". Calls plugdensity::plugin.density() from 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")

Meta Information

Parameters

IdTypeDefaultLevels
na.rmlogicalFALSETRUE, FALSE

References

Engel, Joachim, Herrmann, Eva, Gasser, Theo (1994). “An iterative bandwidth selector for kernel estimation of densities and their derivatives.” Journaltitle of Nonparametric Statistics, 4(1), 21--34.

See also

Author

RaphaelS1

Super classes

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

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage


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

learner = mlr3::lrn("dens.plug")
print(learner)
#> <LearnerDensPlugin:dens.plug>: Kernel Density Estimator
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3proba, mlr3extralearners, plugdensity
#> * Predict Type: pdf
#> * Feature types: numeric
#> * Properties: missings

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