mlr_learners_dens.nonpar.Rd
Calls sm::sm.density from package sm.
This Learner can be instantiated via the
dictionary mlr_learners or with the associated
sugar function lrn()
:
mlr_learners$get("dens.nonpar") lrn("dens.nonpar")
Packages: sm
Predict Types: pdf
Feature Types: integer, numeric
Properties: weights
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.
RaphaelS1
mlr3::Learner
-> mlr3proba::LearnerDens
-> LearnerDensNonparametric
new()
Creates a new instance of this R6 class.
LearnerDensNonparametric$new()
clone()
The objects of this class are cloneable with this method.
LearnerDensNonparametric$clone(deep = FALSE)
deep
Whether to make a deep clone.
# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("dens.nonpar")) print(learner)#> <LearnerDensNonparametric:dens.nonpar> #> * Model: - #> * Parameters: list() #> * Packages: sm #> * Predict Type: pdf #> * Feature types: integer, numeric #> * Properties: weights# available parameters: learner$param_set$ids()#> [1] "h" "group" "delta" "h.weights" "hmult" "method" #> [7] "positive" "verbose"