A LearnerClust for PAM clustering implemented in cluster::pam()
.
cluster::pam()
doesn't have a default value for the number of clusters.
Therefore, the k
parameter which correponds to the number
of clusters here is set to 2 by default.
The predict method uses clue::cl_predict()
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$get("clust.pam") lrn("clust.pam")
mlr3::Learner
-> mlr3cluster::LearnerClust
-> LearnerClustPAM
new()
Creates a new instance of this R6 class.
LearnerClustPAM$new()
clone()
The objects of this class are cloneable with this method.
LearnerClustPAM$clone(deep = FALSE)
deep
Whether to make a deep clone.
#> <LearnerClustPAM:clust.pam> #> * Model: - #> * Parameters: k=2 #> * Packages: cluster #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, partitional# available parameters: learner$param_set$ids()#> [1] "k" "metric" "medoids" "stand" "do.swap" "pamonce" #> [7] "trace.lev"