  Using the ESO-Sculptor galaxy redshift survey data (ESS), we have extensively
tested the Principal Components Analysis (PCA) method to perform the spectral
classification of galaxies with $z \la$ 0.5. This method allows us to classify
all galaxies in an ordered and continuous spectral sequence, which is strongly
correlated with the morphological type. The PCA allows to quantify the
systematic physical properties of the galaxies in the sample, like the
different stellar contributions to the observed light as well as the stellar
formation history. We also examine the influence of the emission lines, and the
signal-to-noise ratio of the data. This analysis shows that the emission lines
play a significant role in the spectral classification, by tracing the activity
and abnormal spectral features of the observed sample. The PCA also provides a
powerful tool to filter the noise which is carried by the ESS spectra. By
comparison of the ESS PCA spectral sequence with that for a selected sample of
Kennicutt galaxies (Kennicutt 1992a), we find that the ESS sample contains 26%
of E/S0, 71% of Sabc and 3% of Sm/Irr. The type fractions for the ESS show no
significant changes in the redshift interval $z \sim 0.1-0.5$, and are
comparable to those found in other galaxy surveys at intermediate redshift. The
PCA can be used independently from any set of synthetic templates, providing a
completely objective and unsupervised method to classify spectra. We compare
the classification of the ESS sample given by the PCA, with a $\chi^2$ test
between the ESS sample and galaxy templates from Kennicutt (Kennicutt 1992a),
and obtain results in good agreement. The PCA results are also in agreement
with the visual morphological classification carried out for the 35 brightest
galaxies in the survey.
