Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Choosing the number of clusters in a finite mixture model using an exact
  Integrated Completed Likelihood criterion   The integrated completed likelihood (ICL) criterion has proven to be a very
popular approach in model-based clustering through automatically choosing the
number of clusters in a mixture model. This approach effectively maximises the
complete data likelihood, thereby including the allocation of observations to
clusters in the model selection criterion. However for practical implementation
one needs to introduce an approximation in order to estimate the ICL. Our
contribution here is to illustrate that through the use of conjugate priors one
can derive an exact expression for ICL and so avoiding any approximation.
Moreover, we illustrate how one can find both the number of clusters and the
best allocation of observations in one algorithmic framework. The performance
of our algorithm is presented on several simulated and real examples.

10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
2
The categories of this paper are: math
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat