Calls np::npudens from package np.

Dictionary

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

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

Traits

  • Packages: np

  • Predict Types: pdf

  • Feature Types: integer, numeric

  • Properties:

References

Li, Q. and J.S. Racine (2003), “Nonparametric estimation of distributions with categorical and continuous data,” Journal of Multivariate Analysis, 86, 266-292.

See also

Author

RaphaelS1

Super classes

mlr3::Learner -> mlr3proba::LearnerDens -> LearnerDensMixed

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerDensMixed$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerDensMixed$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.mixed")) print(learner)
#> <LearnerDensMixed:dens.mixed> #> * Model: - #> * Parameters: list() #> * Packages: np #> * Predict Type: pdf #> * Feature types: integer, numeric #> * Properties: -
# available parameters: learner$param_set$ids()
#> [1] "bws" "ckertype" "bwscaling" #> [4] "bwmethod" "bwtype" "bandwidth.compute" #> [7] "ckerorder" "remin" "itmax" #> [10] "nmulti" "ftol" "tol" #> [13] "small" "lbc.dir" "dfc.dir" #> [16] "cfac.dir" "initc.dir" "lbd.dir" #> [19] "hbd.dir" "dfac.dir" "initd.dir" #> [22] "lbc.init" "hbc.init" "cfac.init" #> [25] "lbd.init" "hbd.init" "dfac.init" #> [28] "ukertype" "okertype"