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Get a subplan for k-means clustering.

Source: R/plans_common_clustering.R
get_clustering_kmeans_subplan.Rd

Besides k-means for selected number of ks, there is also a best k algorithm.

Usage

get_clustering_kmeans_subplan(
  sce_target_name,
  dimred,
  cluster_kmeans_k_enabled,
  cluster_kmeans_k,
  cluster_kmeans_kbest_enabled,
  is_integration,
  plots_out_dir
)

Arguments

sce_target_name

A character scalar: name of target representing a SCE object that will be used for k-means clustering.

dimred

A character scalar: which reducedDim() to use for clustering.

cluster_kmeans_k_enabled, cluster_kmeans_kbest_enabled

A logical scalar: if FALSE, disable the selected clustering and set all corresponding targets to NULL.

cluster_kmeans_k

An integer vector: ks for k-means.

is_integration

A logical scalar: if TRUE, clustering results will be named as cluster_int_kmeans_<method>[_k<k>]. If FALSE, they will be named as cluster_kmeans_<method>[_k<k>].

plots_out_dir

A character scalar: path to output directory to save plots (e.g. clustree::clustree()).

Value

drake::drake_plan()