Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Effects of Additional Data on Bayesian Clustering   Hierarchical probabilistic models, such as mixture models, are used for
cluster analysis. These models have two types of variables: observable and
latent. In cluster analysis, the latent variable is estimated, and it is
expected that additional information will improve the accuracy of the
estimation of the latent variable. Many proposed learning methods are able to
use additional data; these include semi-supervised learning and transfer
learning. However, from a statistical point of view, a complex probabilistic
model that encompasses both the initial and additional data might be less
accurate due to having a higher-dimensional parameter. The present paper
presents a theoretical analysis of the accuracy of such a model and clarifies
which factor has the greatest effect on its accuracy, the advantages of
obtaining additional data, and the disadvantages of increasing the complexity.

30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
1
The categories of this paper are: cs
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg