consensus_matrix: Calculate consensus matrix for data perturbation consensus...

In ConsensusClustering: Consensus Clustering

Calculate consensus matrix for data perturbation consensus clustering

Description

Calculate consensus matrix for data perturbation consensus clustering

Usage

consensus_matrix(
  X,
  max.cluster = 5,
  resample.ratio = 0.7,
  max.itter = 100,
  clustering.method = "hclust",
  adj.conv = TRUE,
  verbos = TRUE
)

Arguments

X	adjacency matrix a Nsample x Nsample
max.cluster	maximum number of clusters
resample.ratio	the data ratio to use at each itteration.
max.itter	maximum number of itterations at each max.cluster
clustering.method	base clustering method: c("hclust", "spectral", "pam")
adj.conv	binary value to apply soft thresholding (default=TRUE)
verbos	binary value for verbosity (default=TRUE)

Details

performs data perturbation consensus clustering and obtain consensus matrix Monti et al. (2003) consensus clustering algorithm This function will be removed in the future release and is replaced by consensus_matrix_data_prtrb()

Value

list of consensus matrices for each k

Examples

X = gaussian_clusters()$X
Adj = adj_mat(X, method = "euclidian")
CM = consensus_matrix(Adj, max.cluster=3, max.itter=10, verbos = FALSE)

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