Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Galaxy Types in the Sloan Digital Sky Survey Using Supervised Artificial
  Neural Networks   Supervised artificial neural networks are used to predict useful properties
of galaxies in the Sloan Digital Sky Survey, in this instance morphological
classifications, spectral types and redshifts. By giving the trained networks
unseen data, it is found that correlations between predicted and actual
properties are around 0.9 with rms errors of order ten per cent. Thus, given a
representative training set, these properties may be reliably estimated for
galaxies in the survey for which there are no spectra and without human
intervention.

30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex