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.
This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn()
:
mlr_learners$get("clust.em") lrn("clust.em")
mlr3::Learner
-> mlr3cluster::LearnerClust
-> LearnerClustEM
new()
Creates a new instance of this R6 class.
LearnerClustEM$new()
clone()
The objects of this class are cloneable with this method.
LearnerClustEM$clone(deep = FALSE)
deep
Whether to make a deep clone.
#> <LearnerClustEM:clust.em> #> * Model: - #> * Parameters: list() #> * Packages: RWeka #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, partitional# available parameters: learner$param_set$ids()#> [1] "I" "ll_cv" "ll_iter" #> [4] "M" "max" "N" #> [7] "num_slots" "S" "X" #> [10] "K" "V" "output_debug_info"