Farthest First Clustering Learner

A LearnerClust for Farthest First clustering implemented in RWeka::FarthestFirst(). The predict method uses RWeka::predict.Weka_clusterer() to compute the cluster memberships for new data.

Dictionary

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

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

Meta Information

• Task type: “clust”

• Predict Types: “partition”

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

• Required Packages: mlr3, mlr3cluster, RWeka

Parameters

Id	Type	Default	Levels	Range
N	integer	2		\([1, \infty)\)
S	integer	1		\([1, \infty)\)
output_debug_info	logical	FALSE	TRUE, FALSE	-

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustFF

Methods

Public methods

• LearnerClustFarthestFirst$new()

• LearnerClustFarthestFirst$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$format()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$print()
• mlr3::Learner$train()
• mlr3cluster::LearnerClust$reset()

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Method new()

Creates a new instance of this R6 class.

Usage

LearnerClustFarthestFirst$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClustFarthestFirst$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (FALSE) {
if (requireNamespace("RWeka")) {
  learner = mlr3::lrn("clust.ff")
  print(learner)

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