Revisiting the Hubble sequence in the SDSS DR7 spectroscopic sample: a
  publicly available bayesian automated classification
  We present an automated morphological classification in 4 types
(E,S0,Sab,Scd) of ~700.000 galaxies from the SDSS DR7 spectroscopic sample
based on support vector machines. The main new property of the classification
is that we associate to each galaxy a probability of being in the four
morphological classes instead of assigning a single class. The classification
is therefore better adapted to nature where we expect a continuos transition
between different morphological types. The algorithm is trained with a visual
classification and then compared to several independent visual classifications
including the Galaxy Zoo first release catalog. We find a very good correlation
between the automated classification and classical visual ones. The compiled
catalog is intended for use in different applications and can be downloaded at
http://gepicom04.obspm.fr/sdss_morphology/Morphology_2010.html and soon from
the CasJobs database.
