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Performs perturbation-based clustering to find optimal k.

Usage

perturbation_clustering(
  data,
  kMin = 2,
  kMax = 5,
  k = NULL,
  n_iter = 50,
  clustering_method = "kmeans",
  verbose = FALSE
)

Arguments

data

Data matrix (samples x features).

kMin

Minimum number of clusters (default: 2).

kMax

Maximum number of clusters (default: 5).

k

Fixed number of clusters (optional).

n_iter

Number of perturbation iterations (default: 50).

clustering_method

Clustering method: "kmeans", "hclust", "pam".

verbose

Print progress.

Value

List with k, cluster, origS, pertS.