mlr_learners_clust.SimpleKMeans: K-Means Clustering Learner from Weka

mlr_learners_clust.SimpleKMeansR Documentation

K-Means Clustering Learner from Weka

Description

A LearnerClust for Simple K Means clustering implemented in RWeka::SimpleKMeans(). 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.SimpleKMeans")
lrn("clust.SimpleKMeans")

Meta Information

  • Task type: “clust”

  • Predict Types: “partition”

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

  • Required Packages: mlr3, mlr3cluster, RWeka

Parameters

Id Type Default Levels Range
A untyped weka.core.EuclideanDistance -
C logical FALSE TRUE, FALSE -
fast logical FALSE TRUE, FALSE -
I integer 100 [1, Inf)
init integer 0 [0, 3]
M logical FALSE TRUE, FALSE -
max_candidates integer 100 [1, Inf)
min_density integer 2 [1, Inf)
N integer 2 [1, Inf)
num_slots integer 1 [1, Inf)
O logical FALSE TRUE, FALSE -
periodic_pruning integer 10000 [1, Inf)
S integer 10 [0, Inf)
t2 numeric -1 (-Inf, Inf)
t1 numeric -1.5 (-Inf, Inf)
V logical FALSE TRUE, FALSE -
output_debug_info logical FALSE TRUE, FALSE -

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustSimpleKMeans

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
LearnerClustSimpleKMeans$new()

Method clone()

The objects of this class are cloneable with this method.

Usage
LearnerClustSimpleKMeans$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

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

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

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