A LearnerClust for agglomerative hierarchical clustering implemented in stats::hclust(). Difference Calculation is done by stats::dist()

Dictionary

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

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

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustHclust

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClustHclust$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClustHclust$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

learner = mlr3::lrn("clust.hclust") print(learner)
#> <LearnerClustHclust:clust.hclust> #> * Model: - #> * Parameters: k=2, distmethod=euclidean #> * Packages: - #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, hierarchical
# available parameters: learner$param_set$ids()
#> [1] "method" "members" "distmethod" "diag" "upper" #> [6] "p" "k"