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Hierarchical (Agglomerative) Clustering

Source: R/hier_clust.R
hier_clust.Rd

hier_clust() defines a model that fits clusters based on a distance-based dendrogram

Usage

hier_clust(
  mode = "partition",
  engine = "stats",
  num_clusters = NULL,
  cut_height = NULL,
  linkage_method = "complete"
)

Arguments

mode

A single character string for the type of model. The only possible value for this model is "partition".

engine

A single character string specifying what computational engine to use for fitting. Possible engines are listed below. The default for this model is "stats".

num_clusters

Positive integer, number of clusters in model (optional).

cut_height

Positive double, height at which to cut dendrogram to obtain cluster assignments (only used if num_clusters is NULL)

linkage_method

the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).

Value

A hier_clust cluster specification.

Examples

# Show all engines
modelenv::get_from_env("hier_clust")
#> # A tibble: 1 × 2
#>   engine mode     
#>   <chr>  <chr>    
#> 1 stats  partition

hier_clust()
#> Hierarchical Clustering Specification (partition)
#> 
#> Main Arguments:
#>   linkage_method = complete
#> 
#> Computational engine: stats 
#>