Gaussian Mixture Models-Based Clustering Learner
Source:R/LearnerClustMclust.R
mlr_learners_clust.mclust.Rd
A LearnerClust for model-based clustering implemented in mclust::Mclust()
.
The predict method uses mclust::predict.Mclust()
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()
:
$get("clust.mclust")
mlr_learnerslrn("clust.mclust")
Meta Information
Task type: “clust”
Predict Types: “partition”, “prob”
Feature Types: “logical”, “integer”, “numeric”
Required Packages: mlr3, mlr3cluster, mclust
Parameters
Id | Type | Default |
G | untyped | c , 1:9 |
modelNames | untyped | - |
prior | untyped | - |
control | untyped | mclust::emControl |
initialization | untyped | - |
x | untyped | - |
Super classes
mlr3::Learner
-> mlr3cluster::LearnerClust
-> LearnerClustMclust
Examples
if (requireNamespace("mclust")) {
learner = mlr3::lrn("clust.mclust")
print(learner)
# available parameters:
learner$param_set$ids()
}
#> <LearnerClustMclust:clust.mclust>: Gaussian Mixture Models Clustering
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3cluster, mclust
#> * Predict Types: [partition], prob
#> * Feature Types: logical, integer, numeric
#> * Properties: complete, fuzzy, partitional
#> [1] "G" "modelNames" "prior" "control"
#> [5] "initialization" "x"