A LearnerClust for divisive hierarchical clustering implemented in cluster::diana(). The predict method uses stats::cutree() which cuts the tree resulting from hierarchical clustering into specified number of groups (see parameter k). The default value for k is 2.

Dictionary

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

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

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustDiana

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClustDiana$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClustDiana$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

learner = mlr3::lrn("clust.diana") print(learner)
#> <LearnerClustDiana:clust.diana> #> * Model: - #> * Parameters: k=2 #> * Packages: cluster #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, hierarchical
# available parameters: learner$param_set$ids()
#> [1] "metric" "stand" "trace.lev" "k"