GMMClustering {sharp} | R Documentation |
Model-based clustering
Description
Runs clustering with Gaussian Mixture Models (GMM) using implementation from
Mclust
. This function is not using stability.
Usage
GMMClustering(xdata, nc = NULL, ...)
Arguments
xdata |
data matrix with observations as rows and variables as columns. |
nc |
matrix of parameters controlling the number of clusters in the
underlying algorithm specified in |
... |
additional parameters passed to |
Value
A list with:
comembership |
an array of binary and symmetric co-membership matrices. |
weights |
a matrix of median weights by feature. |
See Also
Other clustering algorithms:
DBSCANClustering()
,
HierarchicalClustering()
,
KMeansClustering()
,
PAMClustering()
Examples
# Data simulation
set.seed(1)
simul <- SimulateClustering(n = c(10, 10), pk = 50)
# Clustering using Gaussian Mixture Models
mygmm <- GMMClustering(xdata = simul$data, nc = seq_len(30))
[Package sharp version 1.4.6 Index]