mlr_learners_clust.diana | R Documentation |
A LearnerClust for divisive hierarchical clustering implemented in cluster::diana()
.
The predict method uses stats::cutree()
which cuts the tree resulting from
hierarchical clustering into specified number of groups (see parameter k
).
The default value for k
is 2.
This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn()
:
mlr_learners$get("clust.diana") lrn("clust.diana")
Task type: “clust”
Predict Types: “partition”
Feature Types: “logical”, “integer”, “numeric”
Required Packages: mlr3, mlr3cluster, cluster
Id | Type | Default | Levels | Range |
metric | character | euclidean | euclidean, manhattan | - |
stand | logical | FALSE | TRUE, FALSE | - |
trace.lev | integer | 0 | [0, \infty) |
|
k | integer | 2 | [1, \infty) |
|
mlr3::Learner
-> mlr3cluster::LearnerClust
-> LearnerClustDiana
new()
Creates a new instance of this R6 class.
LearnerClustDiana$new()
clone()
The objects of this class are cloneable with this method.
LearnerClustDiana$clone(deep = FALSE)
deep
Whether to make a deep clone.
if (requireNamespace("cluster")) {
learner = mlr3::lrn("clust.diana")
print(learner)
# available parameters:
learner$param_set$ids()
}
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