Expectation-Maximization Clustering Learner

A LearnerClust for Expectation-Maximization clustering implemented in RWeka::list_Weka_interfaces(). 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.em")
lrn("clust.em")

Meta Information

• Task type: “clust”

• Predict Types: “partition”

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

• Required Packages: mlr3, mlr3cluster, RWeka

Parameters

Id	Type	Default	Levels	Range
I	integer	100		\([1, \infty)\)
ll_cv	numeric	1e-06		\([1e-06, \infty)\)
ll_iter	numeric	1e-06		\([1e-06, \infty)\)
M	numeric	1e-06		\([1e-06, \infty)\)
max	integer	-1		\([-1, \infty)\)
N	integer	-1		\([-1, \infty)\)
num_slots	integer	1		\([1, \infty)\)
S	integer	100		\([0, \infty)\)
X	integer	10		\([1, \infty)\)
K	integer	10		\([1, \infty)\)
V	logical	FALSE	TRUE, FALSE	-
output_debug_info	logical	FALSE	TRUE, FALSE	-

Super classes

mlr3::Learner -> mlr3cluster::LearnerClust -> LearnerClustEM

Methods

Public methods

• LearnerClustEM$new()

• LearnerClustEM$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()

---

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClustEM$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClustEM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

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

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerClustEM:clust.em>: Expectation-Maximization Clustering
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3cluster, RWeka
#> * Predict Types:  [partition]
#> * Feature Types: logical, integer, numeric
#> * Properties: complete, exclusive, partitional
#>  [1] "I"                 "ll_cv"             "ll_iter"          
#>  [4] "M"                 "max"               "N"                
#>  [7] "num_slots"         "S"                 "X"                
#> [10] "K"                 "V"                 "output_debug_info"