  We used the galaxy spectra obtained in the ESO Nearby Abell Cluster Survey
(ENACS) to separate early- and late-type galaxies in the ENACS clusters, by
applying a Principal Component Analysis (PCA) in combination with an Artificial
Neural Network (ANN). We represented the spectra by 15 Principal Components,
which form the input for the ANN. The latter was trained with morphological
types from Dressler, and its success rate was estimated from an independent
testing set of galaxies. The success-rate for an early- (E+S0) vs. late-type
(Sp+Irr) classification is close to 75 %; somewhat higher for the early-type
galaxies, and somewhat lower for the late-type galaxies. Using the results of
the PCA/ANN analysis ('spectral' galaxy types for 3798 galaxies, 57 % of which
are of early type and 43 % of late type) we constructed a composite cluster of
2594 galaxies. The late-type galaxies appear to have a larger line-of-sight
velocity dispersion and are less centrally concentrated than the early-type
galaxies. The late-type galaxies with emission lines (OII, H-beta, OIII) in
their spectra are mostly responsible for this difference. The properties of the
late-type galaxies without emission lines are more like those of the early-type
galaxies than like those of the late-type galaxies with emission lines. The
interpretation of the large velocity dispersion and the extended distribution,
in terms of fairly radial (possibly 'first-approach') orbits is probably linked
primarily to the presence of emission-line gas and much less to galaxy type.
