ConsensusClustering (version 1.5.0)

generate_data_prtrb: Generation mechanism for data perturbation consensus clustering

Description

Generation mechanism for data perturbation consensus clustering

Usage

generate_data_prtrb(
  X,
  cluster.method = "pam",
  k = 3,
  resample.ratio = 0.7,
  rep = 10,
  distance.method = "euclidian",
  adj.conv = TRUE,
  func
)

Value

matrix of clusterings Nsample x Nrepeat

Arguments

X

input data Nsample x Nfeatures

cluster.method

base clustering method: c("hclust", "spectral", "pam", "custom")

k

number of clusters

resample.ratio

the data ratio to use at each itteration.

rep

maximum number of itterations at each max.cluster

distance.method

method for distance calculation: "euclidian", "cosine", "maximum", "manhattan", "canberra", "binary", "minkowski".

adj.conv

binary value to apply soft thresholding (default=TRUE)

func

user-definrd function required if cluster.method = "custom". The function needs two inputs of X and k

Details

Performs clustering on the purturbed samples set Monti et al. (2003) consensus clustering algorithm

Examples

X = gaussian_clusters()$X
Clusters = generate_data_prtrb(X)