mlr_learners_clust.meanshift | R Documentation |
A LearnerClust for Mean Shift clustering implemented in LPCM::ms()
.
There is no predict method for LPCM::ms()
, so the method
returns cluster labels for the 'training' data.
This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn()
:
mlr_learners$get("clust.meanshift") lrn("clust.meanshift")
Task type: “clust”
Predict Types: “partition”
Feature Types: “logical”, “integer”, “numeric”
Required Packages: mlr3, mlr3cluster, LPCM
Id | Type | Default | Range |
h | untyped | - | - |
subset | untyped | - | - |
scaled | integer | 1 | [0, \infty) |
iter | integer | 200 | [1, \infty) |
thr | numeric | 0.01 | (-\infty, \infty) |
mlr3::Learner
-> mlr3cluster::LearnerClust
-> LearnerClustMeanShift
new()
Creates a new instance of this R6 class.
LearnerClustMeanShift$new()
clone()
The objects of this class are cloneable with this method.
LearnerClustMeanShift$clone(deep = FALSE)
deep
Whether to make a deep clone.
if (requireNamespace("LPCM")) {
learner = mlr3::lrn("clust.meanshift")
print(learner)
# available parameters:
learner$param_set$ids()
}
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