ConsensusClustering (version 1.5.0)

consensus_matrix_data_prtrb: Calculate consensus matrix for data perturbation consensus clustering

Description

Calculate consensus matrix for data perturbation consensus clustering

Usage

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

Value

list of consensus matrices for each k

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

Examples

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