data(iris)
# define the algorithm's parameters
algo <- createAlgo()
# keep only 3 variables
model <- list(
Petal.Width = "Gaussian", Petal.Length = "Gaussian",
Sepal.Width = "Gaussian", Sepal.Length = "Gaussian"
)
# run RMixtComp in unsupervised clustering mode + data as matrix
res <- mixtCompLearn(iris, model, algo, nClass = 1:4, nCore = 1)
# plot
plotCrit(res)
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