mlr_learners_clust.diana: Divisive Hierarchical Clustering Learner

mlr_learners_clust.dianaR Documentation

Divisive Hierarchical Clustering Learner

Description

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")

Meta Information

  • Task type: “clust”

  • Predict Types: “partition”

  • Feature Types: “logical”, “integer”, “numeric”

  • Required Packages: mlr3, mlr3cluster, cluster

Parameters

Id Type Default Levels Range
metric character euclidean euclidean, manhattan -
stand logical FALSE TRUE, FALSE -
trace.lev integer 0 [0, Inf)
k integer 2 [1, Inf)

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

if (requireNamespace("cluster")) {
  learner = mlr3::lrn("clust.diana")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}

mlr3cluster documentation built on Aug. 15, 2022, 1:05 a.m.