Revisiting the Hubble sequence in the SDSS DR7 spectroscopic sample: a publicly available bayesian automated classification
Abstract
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.
Keywords
Cite
@article{arxiv.1010.3018,
title = {Revisiting the Hubble sequence in the SDSS DR7 spectroscopic sample: a publicly available bayesian automated classification},
author = {Marc Huertas-Company and J. A. L Aguerri and M. Bernardi and S. Mei and J. Sánchez Almeida},
journal= {arXiv preprint arXiv:1010.3018},
year = {2015}
}
Comments
A&A in press, english corrections from language editor added