A LearnerClust for Mean Shift clustering implemented in LPCM::ms(). There is no predict method for LPCM::ms(), so the method returns cluster labels for the 'training' data.

Dictionary

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

mlr_learners$get("clust.meanshift")
lrn("clust.meanshift")

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustMeanShift

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClustMeanShift$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClustMeanShift$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

learner = mlr3::lrn("clust.meanshift") print(learner)
#> <LearnerClustMeanShift:clust.meanshift> #> * Model: - #> * Parameters: list() #> * Packages: LPCM #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, partitional
# available parameters: learner$param_set$ids()
#> [1] "h" "subset" "scaled" "iter" "thr"