We have applied ClassX, an oblique decision tree classifier optimized for
astronomical analysis, to the homogeneous multicolor imaging data base of the
Sloan Digital Sky Survey (SDSS), training the software on subsets of SDSS
objects whose nature is precisely known via spectroscopy. We find that the
software, using photometric data only, correctly classifies a very large
fraction of the objects with existing SDSS spectra, both stellar and
extragalactic. ClassX also accurately predicts the redshifts of both normal and
active galaxies in SDSS. To illustrate ClassX applications in SDSS research, we
(a) derive the object content of the SDSS DR2 photometric catalog and (b)
provide a sample catalog of resolved SDSS objects that contains a large number
of candidate AGN galaxies, 27,000, along with 63,000 candidate normal galaxies
at magnitudes substantially fainter than typical magnitudes of SDSS
spectroscopic objects. The surface density of AGN selected by ClassX to i~19 is
in agreement with that quoted by SDSS. When ClassX is applied to the
photometric data fainter than the SDSS spectroscopic limit, the inferred
surface density of AGN rises sharply, as expected. The ability of the
classifier to accurately constrain the redshifts of huge numbers (ultimately ~
10^7) of active galaxies in the photometric data base promises new insights
into fundamental issues of AGN research, such as the evolution of the AGN
luminosity function with cosmic time, the starburst--AGN connection, and
AGN--galactic morphology relationships.Comment: Accepted for publication in The Astronomical Journal, Vol. 130, 2005;
33 pages, 10 figures, 5 tables, AASTeX v5.0. Table 5 will be electronic in
the published journal, but available now at
http://www-int.stsci.edu/~margon/table5.ascii and
http://www-int.stsci.edu/~margon/table5.ascii.g