multiview_clusters {ConsensusClustering}

Generate multiview clusters from Gaussian distributions with randomly generated parameters

Description

Generate multiview clusters from Gaussian distributions with randomly generated parameters

Usage

multiview_clusters(
  n = c(50, 50),
  hidden.dim = 2,
  observed.dim = c(2, 2, 3),
  sd.max = 0.1,
  sd.noise = 0.01,
  hidden.r.range = c(0.1, 1)
)

Arguments

n

vector of number of data points in each cluster The length of n should be equal to the number of clusters.

hidden.dim

scaler value of dimensions of the hidden state

observed.dim

vector of number of dimensions of the generate clusters. The length of observed.dim should be equal to the number of clusters.

sd.max

maximum standard deviation of clusters

sd.noise

standard deviation of the added noise

hidden.r.range

the range (min, max) of distance of cluster centers from the origin in the hidden space.

Value

a list of data points (X) and cluster labels (class)

Examples

data = multiview_clusters()