hir_clust_from_adj_mat: Hierarchical clustering from adjacency matrix

In ConsensusClustering: Consensus Clustering

Hierarchical clustering from adjacency matrix

Description

Hierarchical clustering from adjacency matrix

Usage

hir_clust_from_adj_mat(
  adj.mat,
  k = 2,
  alpha = 1,
  adj.conv = TRUE,
  method = "ward.D"
)

Arguments

adj.mat	adjacency matrix
k	number of clusters (default=2)
alpha	soft threshold (considered if adj.conv = TRUE) (default=1)
adj.conv	binary value to apply soft thresholding (default=TRUE)
method	distance method (default: ward.D)

Details

apply PAM (k-medoids) clustering on the adjacency matrix

Value

vector of clusters

Examples

Adj_mat = rbind(c(0.0,0.9,0.0),
                c(0.9,0.0,0.2),
                c(0.0,0.2,0.0))
hir_clust_from_adj_mat(Adj_mat)

ConsensusClustering documentation built on Sept. 11, 2024, 6:38 p.m.