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.

## Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

### Method clone()

The objects of this class are cloneable with this method.

LearnerClustPAM$clone(deep = FALSE) #### Arguments deep Whether to make a deep clone. ## Examples learner = mlr3::lrn("clust.pam") print(learner) #> <LearnerClustPAM:clust.pam> #> * Model: - #> * Parameters: k=2 #> * Packages: cluster #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, partitional # available parameters: learner$param_set\$ids()
#> [1] "k"         "metric"    "medoids"   "stand"     "do.swap"   "pamonce"
#> [7] "trace.lev"