A Post-Processing Method of Classification Rule on Stellar Spectra
Automatic classification and analysis of observational data is of great significance along with the gradual implementation of LAMOST Survey, which will obtain a large number of spectra data. In classification rules extracted, there is often a great deal of redundancy which will reduce
the classification efficiency and quality seriously. In the present paper, a post-processing method of star spectra classification rule based on predicate logic is presented by using predication to describe the classification rules and logical reasoning to eliminate redundant rules. In the
end, some experimental results on LAMOST’s stellar spectra data show that, with no classification accuracy reduction, the efficiency of auto classification is significantly improved.
Keywords: Classification rule; Data mining; Post processing; Predicate logic; Stellar spectra data
Document Type: Research Article
Publication date: 01 January 2013
- Spectroscopy and Spectral Analysis, founded in 1981, is sponsored by the Chinese Central Iron & Steel Research Institute. "Spectroscopy and Spectral Analysis" has been indexed in SCI(1999), Ei(1992), MEDLINE(1999), and AJ (1999). "Spectroscopy and Spectral Analysis" publishes original contributions on various fields in Spectroscopy, including research results on laser spectroscopy, IR, Ramn, UV/Vis, Optical Emission, Absorption and Fluorescence spectroscopy, X-ray Fluorescence, and Spectrochemical Analysis, as well as Reseach paper, Research notes, Experimental Technique and Instrument, Review and Progress on the latest development of spectroscopy and spectrochemical anlysis, etc. "Spectroscopy and Spectral Analysis" is published monthly by Peking University Press with book sizes of large 16-mo format , and 292 pages per issue.
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