  Cross-correlating the XMM-Newton 2XMMi-DR3 catalog with the Sloan Digital Sky
Survey (SDSS) Data Release 8, we obtain one of the largest X-ray/optical
catalogs and explore the distribution of various classes of X-ray emitters in
the multidimensional photometric parameter space. Quasars and galaxies occupy
different zones while stars scatter in them. However, X-ray active stars have a
certain distributing rule according to spectral types. The earlier the type of
stars, the stronger X-ray emitting. X-ray active stars have a similar
distribution to most of stars in the g-r versus r-i diagram. Based on the
identified samples with SDSS spectral classification, a random forest algorithm
for automatic classification is performed. The result shows that the
classification accuracy of quasars and galaxies adds up to more than 93.0%
while that of X-ray emitting stars only amounts to 45.3%. In other words, it is
easy to separate quasars and galaxies, but it is difficult to discriminate
X-ray active stars from quasars and galaxies. If we want to improve the
accuracy of automatic classification, it is necessary to increase the number of
X-ray emitting stars, since the majority of X-ray emitting sources are quasars
and galaxies. The results obtained here will be used for the optical spectral
survey performed by the Large sky Area Multi-Object fiber Spectroscopic
Telescope (LAMOST, also named the Guo Shou Jing Telescope), which is a Chinese
national scientific research facility operated by the National Astronomical
Observatories, Chinese Academy of Sciences.
