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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.
# S3 method for clustCombi
plot(x, what = c("classification", "entropy", "tree"), …)
Object returned by clustCombi
function.
Type of plot.
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.
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.
# NOT RUN {
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)
# }
# NOT RUN {
# }
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