Description
We have applied ClassX, an oblique decision tree classifier optimized for astronomical analysis, to the homogeneous multicolor imaging database 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 (1) derive the object content of the SDSS Data Release 2 photometric catalog and (2) provide a sample catalog of resolved SDSS objects that contains a large number of candidate active galactic nucleus (AGN) galaxies (27,000), along with 63,000 candidate normal galaxies at magnitudes substantially fainter than the typical magnitudes of SDSS spectroscopic objects.
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