mlr_learners_clust.xmeans {mlr3cluster}R Documentation

X-means Clustering Learner

Description

A LearnerClust for X-means clustering implemented in RWeka::XMeans(). 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.xmeans")
lrn("clust.xmeans")

Meta Information

Parameters

Id Type Default Levels Range
B numeric 1 [0, \infty)
C numeric 0 [0, \infty)
D untyped weka.core.EuclideanDistance -
H integer 4 [1, \infty)
I integer 1 [1, \infty)
J integer 1000 [1, \infty)
K untyped -
L integer 2 [1, \infty)
M integer 1000 [1, \infty)
S integer 10 [1, \infty)
U integer 0 [0, \infty)
use_kdtree logical FALSE TRUE, FALSE -
N untyped - -
O untyped - -
Y untyped - -
output_debug_info logical FALSE TRUE, FALSE -

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustXMeans

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
LearnerClustXMeans$new()

Method clone()

The objects of this class are cloneable with this method.

Usage
LearnerClustXMeans$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Witten, H I, Frank, Eibe (2002). “Data mining: practical machine learning tools and techniques with Java implementations.” Acm Sigmod Record, 31(1), 76–77.

Pelleg, Dan, Moore, W A, others (2000). “X-means: Extending k-means with efficient estimation of the number of clusters.” In Icml, volume 1, 727–734.

See Also

Other Learner: mlr_learners_clust.MBatchKMeans, mlr_learners_clust.SimpleKMeans, mlr_learners_clust.agnes, mlr_learners_clust.ap, mlr_learners_clust.cmeans, mlr_learners_clust.cobweb, mlr_learners_clust.dbscan, mlr_learners_clust.dbscan_fpc, mlr_learners_clust.diana, mlr_learners_clust.em, mlr_learners_clust.fanny, mlr_learners_clust.featureless, mlr_learners_clust.ff, mlr_learners_clust.hclust, mlr_learners_clust.hdbscan, mlr_learners_clust.kkmeans, mlr_learners_clust.kmeans, mlr_learners_clust.mclust, mlr_learners_clust.meanshift, mlr_learners_clust.optics, mlr_learners_clust.pam

Examples

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

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

[Package mlr3cluster version 0.1.9 Index]