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mlr3cluster

Package website:release |dev

Cluster analysis formlr3.

mlr3cluster is an extension package for clusteranalysis within themlr3 ecosystem. Itis a successor of clustering capabilities ofmlr2.

Installation

Install the last release from CRAN:

install.packages("mlr3cluster")

Install the development version from GitHub:

# install.packages("pak")pak::pak("mlr-org/mlr3cluster")

Feature Overview

The current version ofmlr3cluster contains:

• A selection of 24 clustering learners that represent a wide varietyof clusterers: partitional, hierarchical, fuzzy, etc.
• A selection of 4 performance measures
• Two built-in tasks to get started with clustering

Also, the package is integrated withmlr3viz whichenables you to create great visualizations with just one line ofcode!

Cluster Analysis

Cluster Learners

Cluster Measures

Example

library(mlr3)library(mlr3cluster)task=tsk("usarrests")task#>#> ── <TaskClust> (50x4): US Arrests ──────────────────────────────────────────────#> • Target:#> • Properties: -#> • Features (4):#>   • int (2): Assault, UrbanPop#>   • dbl (2): Murder, Rapelearner=lrn("clust.kmeans")prediction= learner$train(task)$predict(task)measures=msrs(c("clust.wss","clust.silhouette"))prediction$score(measures, task)#>        clust.wss clust.silhouette#>     9.639903e+04     5.926554e-01

More Resources

Check out theblogpostfor a more detailed introduction to the package. Also,mlr3bookhas a section on clustering.

Future Plans

• Add more learners and measures
• Integrate the package withmlr3pipelines(work in progress)

If you have any questions, feedback or ideas, feel free to open anissuehere.