dm13450/dirichletprocess

plot's dimension in a clustering of multivariate case.

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rhyeu commented

Hello, I am Rhyeu in South Korea.

First of all, thanks for this awsome package!
I want to employ bayesian clustering method to some data but I could not find a package to fit them, not this package.

So, I have been tested some functions in it. and I have had a question.

when I exploit this function in multivariate data's clustering, what dimensions are applied to draw a plot??

In dummy case to be concrete,
I have tried to use 'DirichletProcessMvnormal' and 'Fit' in Fisher's iris data.

which dimensions are used in this plot? first and second loadings in PCA??
or other dimension that function have found?

I have started to study nonparametric bayesian clustering...
I have already check 'Vignettes' and reference manual but I could not find the dimension's definition..
please pardon me if I skipped your work defining that....

the dummy code is as follow.
Thanks!

data(iris)

iris_scale = scale(iris[,1:4])
dpCluster = DirichletProcessMvnormal(iris_scale)
dpCluster = Fit(dpCluster, 1000, progressBar = FALSE) 

plot(dpCluster)

It'll plot the first two dimensions x = iris_scale[,1], y = iris_scale[,2]

Thanks for using the package!