mclust: plot.clustCombi – R documentation

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plot.clustCombi

Plot Combined Clusterings Results

Description

Plot combined clusterings results: classifications corresponding to Mclust/BIC and to the hierarchically combined classes, "entropy plots" to help to select a number of classes, and the tree structure obtained from combining mixture components.

Usage

## S3 method for class 'clustCombi'
plot(x, what = c("classification", "entropy", "tree"), ...)

Arguments

`x`	Object returned by `clustCombi` function.
`what`	Type of plot.
`...`	Other arguments to be passed to other functions: `combiPlot`, `entPlot`, `combiTree`. Please see the corresponding documentations.

Value

Classifications are plotted with combiPlot, which relies on the Mclust plot functions. Entropy plots are plotted with entPlot and may help to select a number of classes: please see the article cited in the references. Tree plots are produced by combiTree and graph the tree structure implied by the clusters combining process.

Author(s)

J.-P. Baudry, A. E. Raftery, L. Scrucca

References

J.-P. Baudry, A. E. Raftery, G. Celeux, K. Lo and R. Gottardo (2010). Combining mixture components for clustering. Journal of Computational and Graphical Statistics, 19(2):332-353.

Examples

data(Baudry_etal_2010_JCGS_examples)

## 1D Example 
output <- clustCombi(data = Test1D, G=1:15)

# plots the hierarchy of combined solutions, then some "entropy plots" which 
# may help one to select the number of classes (please see the article cited 
# in the references)
plot(output) 

## 2D Example 
output <- clustCombi(data = ex4.1) 

# plots the hierarchy of combined solutions, then some "entropy plots" which 
# may help one to select the number of classes (please see the article cited 
# in the references)
plot(output) 

## 3D Example 
output <- clustCombi(data = ex4.4.2)

# plots the hierarchy of combined solutions, then some "entropy plots" which 
# may help one to select the number of classes (please see the article cited 
# in the references)
plot(output)

mclust

Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

v5.4.10

GPL (>= 2)

Authors

Chris Fraley [aut], Adrian E. Raftery [aut] (<https://orcid.org/0000-0002-6589-301X>), Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>), Thomas Brendan Murphy [ctb] (<https://orcid.org/0000-0002-5668-7046>), Michael Fop [ctb] (<https://orcid.org/0000-0003-3936-2757>)

Initial release

2022-05-20