X-means Cluster Learner

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")

Super classes

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

Methods

Public methods

• LearnerClustXMeans$new()

• LearnerClustXMeans$clone()

Inherited methods

• 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

LearnerClustXMeans$new()

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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.

Examples

learner = mlr3::lrn("clust.xmeans")
print(learner)
#> <LearnerClustXMeans:clust.xmeans>
#> * Model: -
#> * Parameters: list()
#> * Packages: RWeka
#> * Predict Type: partition
#> * Feature types: logical, integer, numeric
#> * Properties: complete, exclusive, partitional

# available parameters:
learner$param_set$ids()
#>  [1] "B"                 "C"                 "D"                
#>  [4] "H"                 "I"                 "J"                
#>  [7] "K"                 "L"                 "M"                
#> [10] "S"                 "U"                 "use_kdtree"       
#> [13] "N"                 "O"                 "Y"                
#> [16] "output_debug_info"