From 9829f6a181046984f5e3d39da37bc1fa75b1b60e Mon Sep 17 00:00:00 2001 From: Maximilian Muecke Date: Sun, 17 Nov 2024 15:18:37 +0100 Subject: [PATCH] docs(readme): rebuild readme --- README.Rmd | 1 - README.md | 78 ++++++++++++++++++++++++++++-------------------------- 2 files changed, 40 insertions(+), 39 deletions(-) diff --git a/README.Rmd b/README.Rmd index 321d4e8c..04b1f986 100644 --- a/README.Rmd +++ b/README.Rmd @@ -16,7 +16,6 @@ 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)] -lrn_clust = lrn_clust[key != c("clust.bico", "clust.birch")] # remove after cran release ``` # mlr3cluster diff --git a/README.md b/README.md index d5ac5d86..3caa35f8 100644 --- a/README.md +++ b/README.md @@ -41,10 +41,10 @@ pak::pak("mlr-org/mlr3cluster") The current version of **mlr3cluster** contains: -- A selection of 22 clustering learners that represent a wide variety - of clusterers: partitional, hierarchical, fuzzy, etc. -- A selection of 4 performance measures -- Two built-in tasks to get started with clustering +- A selection of 24 clustering learners that represent a wide variety of + 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 with **[mlr3viz](https://github.com/mlr-org/mlr3viz)** which enables you to @@ -54,39 +54,41 @@ create great visualizations with just one line of code! ### Cluster Learners -| Key | Label | Packages | -|:------------------------------------------------------------------------------------------------|:--------------------------------------|:----------------------------------------------------------| -| [clust.MBatchKMeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.MBatchKMeans) | Mini Batch K-Means | [ClusterR](https://cran.r-project.org/package=ClusterR) | -| [clust.SimpleKMeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.SimpleKMeans) | K-Means (Weka) | [RWeka](https://cran.r-project.org/package=RWeka) | -| [clust.agnes](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.agnes) | Agglomerative Hierarchical Clustering | [cluster](https://cran.r-project.org/package=cluster) | -| [clust.ap](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.ap) | Affinity Propagation Clustering | [apcluster](https://cran.r-project.org/package=apcluster) | -| [clust.cmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.cmeans) | Fuzzy C-Means Clustering Learner | [e1071](https://cran.r-project.org/package=e1071) | -| [clust.cobweb](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.cobweb) | Cobweb Clustering | [RWeka](https://cran.r-project.org/package=RWeka) | -| [clust.dbscan](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.dbscan) | Density-Based Clustering | [dbscan](https://cran.r-project.org/package=dbscan) | -| [clust.dbscan_fpc](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.dbscan_fpc) | Density-Based Clustering with fpc | [fpc](https://cran.r-project.org/package=fpc) | -| [clust.diana](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.diana) | Divisive Hierarchical Clustering | [cluster](https://cran.r-project.org/package=cluster) | -| [clust.em](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.em) | Expectation-Maximization Clustering | [RWeka](https://cran.r-project.org/package=RWeka) | -| [clust.fanny](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.fanny) | Fuzzy Analysis Clustering | [cluster](https://cran.r-project.org/package=cluster) | -| [clust.featureless](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.featureless) | Featureless Clustering | | -| [clust.ff](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.ff) | Farthest First Clustering | [RWeka](https://cran.r-project.org/package=RWeka) | -| [clust.hclust](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.hclust) | Agglomerative Hierarchical Clustering | stats | -| [clust.hdbscan](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.hdbscan) | HDBSCAN Clustering | [dbscan](https://cran.r-project.org/package=dbscan) | -| [clust.kkmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.kkmeans) | Kernel K-Means | [kernlab](https://cran.r-project.org/package=kernlab) | -| [clust.kmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.kmeans) | K-Means | stats, [clue](https://cran.r-project.org/package=clue) | -| [clust.mclust](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.mclust) | Gaussian Mixture Models Clustering | [mclust](https://cran.r-project.org/package=mclust) | -| [clust.meanshift](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.meanshift) | Mean Shift Clustering | [LPCM](https://cran.r-project.org/package=LPCM) | -| [clust.optics](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.optics) | OPTICS Clustering | [dbscan](https://cran.r-project.org/package=dbscan) | -| [clust.pam](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.pam) | Partitioning Around Medoids | [cluster](https://cran.r-project.org/package=cluster) | -| [clust.xmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.xmeans) | X-means | [RWeka](https://cran.r-project.org/package=RWeka) | +| Key | Label | Packages | +|:---|:---|:---| +| [clust.MBatchKMeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.MBatchKMeans) | Mini Batch K-Means | [ClusterR](https://cran.r-project.org/package=ClusterR) | +| [clust.SimpleKMeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.SimpleKMeans) | K-Means (Weka) | [RWeka](https://cran.r-project.org/package=RWeka) | +| [clust.agnes](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.agnes) | Agglomerative Hierarchical Clustering | [cluster](https://cran.r-project.org/package=cluster) | +| [clust.ap](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.ap) | Affinity Propagation Clustering | [apcluster](https://cran.r-project.org/package=apcluster) | +| [clust.bico](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.bico) | BICO Clustering | [stream](https://cran.r-project.org/package=stream) | +| [clust.birch](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.birch) | BIRCH Clustering | [stream](https://cran.r-project.org/package=stream) | +| [clust.cmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.cmeans) | Fuzzy C-Means Clustering Learner | [e1071](https://cran.r-project.org/package=e1071) | +| [clust.cobweb](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.cobweb) | Cobweb Clustering | [RWeka](https://cran.r-project.org/package=RWeka) | +| [clust.dbscan](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.dbscan) | Density-Based Clustering | [dbscan](https://cran.r-project.org/package=dbscan) | +| [clust.dbscan_fpc](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.dbscan_fpc) | Density-Based Clustering with fpc | [fpc](https://cran.r-project.org/package=fpc) | +| [clust.diana](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.diana) | Divisive Hierarchical Clustering | [cluster](https://cran.r-project.org/package=cluster) | +| [clust.em](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.em) | Expectation-Maximization Clustering | [RWeka](https://cran.r-project.org/package=RWeka) | +| [clust.fanny](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.fanny) | Fuzzy Analysis Clustering | [cluster](https://cran.r-project.org/package=cluster) | +| [clust.featureless](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.featureless) | Featureless Clustering | | +| [clust.ff](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.ff) | Farthest First Clustering | [RWeka](https://cran.r-project.org/package=RWeka) | +| [clust.hclust](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.hclust) | Agglomerative Hierarchical Clustering | stats | +| [clust.hdbscan](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.hdbscan) | HDBSCAN Clustering | [dbscan](https://cran.r-project.org/package=dbscan) | +| [clust.kkmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.kkmeans) | Kernel K-Means | [kernlab](https://cran.r-project.org/package=kernlab) | +| [clust.kmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.kmeans) | K-Means | stats, [clue](https://cran.r-project.org/package=clue) | +| [clust.mclust](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.mclust) | Gaussian Mixture Models Clustering | [mclust](https://cran.r-project.org/package=mclust) | +| [clust.meanshift](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.meanshift) | Mean Shift Clustering | [LPCM](https://cran.r-project.org/package=LPCM) | +| [clust.optics](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.optics) | OPTICS Clustering | [dbscan](https://cran.r-project.org/package=dbscan) | +| [clust.pam](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.pam) | Partitioning Around Medoids | [cluster](https://cran.r-project.org/package=cluster) | +| [clust.xmeans](https://mlr3cluster.mlr-org.com/reference/mlr_learners_clust.xmeans) | X-means | [RWeka](https://cran.r-project.org/package=RWeka) | ### Cluster Measures -| Key | Label | Packages | -|:--------------------------------------------------------------------------------------------|:----------------------|:------------------------------------------------------| -| [clust.ch](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.ch) | Calinski Harabasz | [fpc](https://cran.r-project.org/package=fpc) | -| [clust.dunn](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.dunn) | Dunn | [fpc](https://cran.r-project.org/package=fpc) | -| [clust.silhouette](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.silhouette) | Silhouette | [cluster](https://cran.r-project.org/package=cluster) | -| [clust.wss](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.wss) | Within Sum of Squares | [fpc](https://cran.r-project.org/package=fpc) | +| Key | Label | Packages | +|:---|:---|:---| +| [clust.ch](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.ch) | Calinski Harabasz | [fpc](https://cran.r-project.org/package=fpc) | +| [clust.dunn](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.dunn) | Dunn | [fpc](https://cran.r-project.org/package=fpc) | +| [clust.silhouette](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.silhouette) | Silhouette | [cluster](https://cran.r-project.org/package=cluster) | +| [clust.wss](https://mlr3cluster.mlr-org.com/reference/mlr_measures_clust.wss) | Within Sum of Squares | [fpc](https://cran.r-project.org/package=fpc) | ## Example @@ -110,10 +112,10 @@ 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) +- 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).