mclust_clust: Model-Based Clustering

In ICSClust: Tandem Clustering with Invariant Coordinate Selection

Model-Based Clustering

Description

Wrapper for performing Model-Based Clustering from mclust::Mclust() allowing noise or not.

Usage

mclust_clust(X, k, clusters_only = FALSE, ...)

rmclust_clust(X, k, clusters_only = FALSE, ...)

Arguments

X	a numeric matrix or data frame of the data. It corresponds to the argument data.
k	the number of clusters searched for. It corresponds to the argument G of function mclust::Mclust().
clusters_only	boolean. If TRUE only the partition of the data is returned as a vector. If FALSE the usual output of the mclust::Mclust() function is returned.
...	other arguments to pass to mclust::Mclust().

Details

• mclust_clust(): does not allow noise

• rmclust_clust(): allows noise

Value

If clusters_only is TRUE a vector of the new partition of the data is returned, i.e a vector of integers (from 1:k) indicating the cluster to which each observation is allocated. 0 indicates trimmed observations.

Otherwise a list is returned with the following components:

clust_method	the name of the clustering method, i.e "rimle".
clusters	the vector of the new partition of the data, i.e a vector of integers (from 1:k) indicating the cluster to which each observation is allocated. 0 indicates outlying observations for rmclust_clust() only.
...	an object of class "mclust"

Author(s)

Aurore Archimbaud

See Also

mclust::Mclust()

Examples

mclust_clust(iris[,1:4], k = 3, clusters_only = TRUE)

ICSClust documentation built on Sept. 21, 2023, 5:07 p.m.