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https://github.com/mlr-org/mlr3cluster

Cluster analysis for mlr3
https://github.com/mlr-org/mlr3cluster

cluster-analysis clustering mlr3 r r-package

Last synced: 4 days ago
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Cluster analysis for mlr3

Host: GitHub
URL: https://github.com/mlr-org/mlr3cluster
Owner: mlr-org
License: lgpl-3.0
Created: 2018-11-16T10:32:38.000Z (about 6 years ago)
Default Branch: main
Last Pushed: 2024-12-09T20:40:47.000Z (13 days ago)
Last Synced: 2024-12-09T21:31:22.342Z (13 days ago)
Topics: cluster-analysis, clustering, mlr3, r, r-package
Language: R
Homepage: https://mlr3cluster.mlr-org.com
Size: 7.68 MB
Stars: 23
Watchers: 14
Forks: 6
Open Issues: 9
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE

Awesome Lists containing this project

README

        ---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

library(data.table)

library(mlr3cluster)

library(mlr3misc)

lrn_clust = as.data.table(mlr3::mlr_learners)[task_type == "clust", .(key, label, packages)]

msr_clust = as.data.table(mlr3::mlr_measures)[task_type == "clust", .(key, label, packages)]

```

# mlr3cluster

Package website: [release](https://mlr3cluster.mlr-org.com/) \| [dev](https://mlr3cluster.mlr-org.com/dev/)

Cluster analysis for **[mlr3](https://github.com/mlr-org/mlr3/)**.

[![r-cmd-check](https://github.com/mlr-org/mlr3cluster/actions/workflows/r-cmd-check.yml/badge.svg)](https://github.com/mlr-org/mlr3cluster/actions/workflows/r-cmd-check.yml)

[![CRAN status](https://www.r-pkg.org/badges/version/mlr3cluster)](https://CRAN.R-project.org/package=mlr3cluster)

[![StackOverflow](https://img.shields.io/badge/stackoverflow-mlr3-orange.svg)](https://stackoverflow.com/questions/tagged/mlr3)

[![Mattermost](https://img.shields.io/badge/chat-mattermost-orange.svg)](https://lmmisld-lmu-stats-slds.srv.mwn.de/mlr_invite/)

**mlr3cluster** is an extension package for cluster analysis within the **[mlr3](https://github.com/mlr-org/mlr3)** ecosystem. It is a successor of clustering capabilities of **[mlr2](https://github.com/mlr-org/mlr)**.

## Installation

Install the last release from CRAN:

```{r, eval = FALSE}

install.packages("mlr3cluster")

```

Install the development version from GitHub:

```{r, eval = FALSE}

# install.packages("pak")

pak::pak("mlr-org/mlr3cluster")

```

## Feature Overview

The current version of **mlr3cluster** contains:

- A selection of `r nrow(lrn_clust)` clustering learners that represent a wide variety of clusterers: partitional, hierarchical, fuzzy, etc.

- A selection of `r nrow(msr_clust)` performance measures

- Two built-in tasks to get started with clustering

Also, the package is integrated with **[mlr3viz](https://github.com/mlr-org/mlr3viz)** which enables you to create great visualizations with just one line of code!

## Cluster Analysis

### Cluster Learners

```{r, echo = FALSE}

cran_pkg = function(pkgs) {

  pkgs = fifelse(

    pkgs %chin% c("stats", "graphics", "datasets"),

    pkgs, sprintf("[%1$s](https://cran.r-project.org/package=%1$s)", pkgs)

  )

  toString(pkgs)

}

lrn_clust[, packages := map(packages, function(x) setdiff(x, c("mlr3", "mlr3cluster")))]

lrn_clust[, `:=`(

  key = sprintf("[%1$s](https://mlr3cluster.mlr-org.com/reference/mlr_learners_%1$s)", key),

  packages = map_chr(packages, cran_pkg)

)]

knitr::kable(lrn_clust, format = "markdown", col.names = tools::toTitleCase(names(lrn_clust)))

```

### Cluster Measures

```{r, echo = FALSE}

msr_clust[, packages := map(packages, function(x) setdiff(x, c("mlr3", "mlr3cluster")))]

msr_clust[, `:=`(

  key = sprintf("[%1$s](https://mlr3cluster.mlr-org.com/reference/mlr_measures_%1$s)", key),

  packages = map_chr(packages, cran_pkg)

)]

knitr::kable(msr_clust, format = "markdown", col.names = tools::toTitleCase(names(msr_clust)))

```

## Example

```{r, eval = FALSE}

library(mlr3)

library(mlr3cluster)

task = tsk("usarrests")

learner = lrn("clust.kmeans")

learner$train(task)

prediction = learner$predict(task = task)

```

## More Resources

Check out the **[blogpost](https://www.r-bloggers.com/2020/10/introducing-mlr3cluster-cluster-analysis-package/)** for a more detailed introduction to the package.

Also, **[mlr3book](https://mlr3book.mlr-org.com/chapters/chapter13/beyond_regression_and_classification.html#sec-cluster)** has a section on clustering.

## Future Plans

- Add more learners and measures

- Integrate the package with **[mlr3pipelines](https://github.com/mlr-org/mlr3pipelines)** (work in progress)

If you have any questions, feedback or ideas, feel free to open an issue [here](https://github.com/mlr-org/mlr3cluster/issues).