  We measure the two-point angular correlation function of a sample of
4,289,223 galaxies with r < 19.4 mag from the Sloan Digital Sky Survey as a
function of photometric redshift, absolute magnitude and colour down to M_r -
5log h = -14 mag. Photometric redshifts are estimated from ugriz model
magnitudes and two Petrosian radii using the artificial neural network package
ANNz, taking advantage of the Galaxy and Mass Assembly (GAMA) spectroscopic
sample as our training set. The photometric redshifts are then used to
determine absolute magnitudes and colours. For all our samples, we estimate the
underlying redshift and absolute magnitude distributions using Monte-Carlo
resampling. These redshift distributions are used in Limber's equation to
obtain spatial correlation function parameters from power law fits to the
angular correlation function. We confirm an increase in clustering strength for
sub-L* red galaxies compared with ~L* red galaxies at small scales in all
redshift bins, whereas for the blue population the correlation length is almost
independent of luminosity for ~L* galaxies and fainter. A linear relation
between relative bias and log luminosity is found to hold down to luminosities
L~0.03L*. We find that the redshift dependence of the bias of the L* population
can be described by the passive evolution model of Tegmark & Peebles (1998). A
visual inspection of a random sample of our r < 19.4 sample of SDSS galaxies
reveals that about 10 per cent are spurious, with a higher contamination rate
towards very faint absolute magnitudes due to over-deblended nearby galaxies.
We correct for this contamination in our clustering analysis.
