Revisiting the Hubble sequence in the SDSS DR7 spectroscopic sample: a publicly available bayesian automated classification

摘要

We present an automated morphological classification in 4 types(E,S0,Sab,Scd) of ~700.000 galaxies from the SDSS DR7 spectroscopic samplebased on support vector machines. The main new property of the classificationis that we associate to each galaxy a probability of being in the fourmorphological classes instead of assigning a single class. The classificationis therefore better adapted to nature where we expect a continuos transitionbetween different morphological types. The algorithm is trained with a visualclassification and then compared to several independent visual classificationsincluding the Galaxy Zoo first release catalog. We find a very good correlationbetween the automated classification and classical visual ones. The compiledcatalog is intended for use in different applications and can be downloaded athttp://gepicom04.obspm.fr/sdss_morphology/Morphology_2010.html and soon fromthe CasJobs database.