Calls sm::sm.density from package sm.

Dictionary

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

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

Traits

  • Packages: sm

  • Predict Types: pdf

  • Feature Types: integer, numeric

  • Properties: weights

References

Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.

See also

Author

RaphaelS1

Super classes

mlr3::Learner -> mlr3proba::LearnerDens -> LearnerDensNonparametric

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerDensNonparametric$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerDensNonparametric$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.nonpar")) print(learner)
#> <LearnerDensNonparametric:dens.nonpar> #> * Model: - #> * Parameters: list() #> * Packages: sm #> * Predict Type: pdf #> * Feature types: integer, numeric #> * Properties: weights
# available parameters: learner$param_set$ids()
#> [1] "h" "group" "delta" "h.weights" "hmult" "method" #> [7] "positive" "verbose"