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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

IdTypeDefaultLevelsRange
Ninteger2\([1, \infty)\)
Sinteger1\([1, \infty)\)
output_debug_infologicalFALSETRUE, FALSE-

Super classes

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

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.


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

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerClustFF:clust.ff>: Farthest First Clustering
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3cluster, RWeka
#> * Predict Types:  [partition]
#> * Feature Types: logical, integer, numeric
#> * Properties: complete, exclusive, partitional
#> [1] "N"                 "S"                 "output_debug_info"