A LearnerClust for agglomerative hierarchical clustering implemented in cluster::agnes(). The predict method uses stats::cutree() which cuts the tree resulting from hierarchical clustering into specified number of groups (see parameter k). The default number for k is 2.

## 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.

LearnerClustAgnes$clone(deep = FALSE) #### Arguments deep Whether to make a deep clone. ## Examples learner = mlr3::lrn("clust.agnes") print(learner) #> <LearnerClustAgnes:clust.agnes> #> * Model: - #> * Parameters: k=2 #> * Packages: cluster #> * Predict Type: partition #> * Feature types: logical, integer, numeric #> * Properties: complete, exclusive, hierarchical # available parameters: learner$param_set\$ids()
#> [1] "metric"     "stand"      "method"     "trace.lev"  "k"
#> [6] "par.method"