Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian Kernel and Mutual $k$-Nearest Neighbor Regression   We propose Bayesian extensions of two nonparametric regression methods which
are kernel and mutual $k$-nearest neighbor regression methods. Derived based on
Gaussian process models for regression, the extensions provide distributions
for target value estimates and the framework to select the hyperparameters. It
is shown that both the proposed methods asymptotically converge to kernel and
mutual $k$-nearest neighbor regression methods, respectively. The simulation
results show that the proposed methods can select proper hyperparameters and
are better than or comparable to the former methods for an artificial data set
and a real world data set.

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The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph