Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Discrete Classification with Principal Component Analysis:
  Discrimination of Giant and Dwarf Spectra in K-stars   We demonstrate the use of a variant of Principal Component Analysis (PCA) for
discrimination problems in astronomy. This variant of PCA is shown to provide
the best linear discrimination between data classes. As a test case, we present
the problem of discrimination between K giant and K dwarf stars from
intermediate resolution spectra near the Mg `b' feature. The discrimination
procedure is trained on a set of 24 standard K giants and 24 standard K dwarfs,
and then used to perform giant - dwarf classification on a sample of
approximately 1500 field K stars of unknown luminosity class which were
initially classified visually. For the highest S/N spectra, the automated
classification agrees very well (at the 90 - 95% level) with the visual
classification. Most importantly, however, the automated method is found to
classify stars in a repeatable fashion, and, according to numerical
experiments, is very robust to signal to noise (S/N) degradation.

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The categories of this paper are: math
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The categories of this paper are: hep-th
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The categories of this paper are: q-fin
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The categories of this paper are: stat
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The categories of this paper are: cs
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The categories of this paper are: nucl-ex
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The categories of this paper are: cond-mat
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The categories of this paper are: solv-int
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The categories of this paper are: hep-lat
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The categories of this paper are: supr-con
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The categories of this paper are: math-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-ex
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The categories of this paper are: physics
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The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg