  Context. Near open clusters as Pleiades, Praesepe and Blanco 1 have been
extensively studied due to their proximity to the Sun. The Gaia data brings the
opportunity to investigate these clusters, since it contains valuable
astrometric and photometric information which can be used to update their
kinematic and stellar properties. Aims. Our goal is to carry out a star
membership study in these nearby open clusters employing an astrometric model
with proper motions and an unsupervised clustering machine learning algorithm
using positions, proper motions and parallaxes. The star members are selected
from the cross-matching between both methods. Methods. We use the Gaia DR3
catalogue to determine star members using two approaches: a classical Bayesian
model and the unsupervised machine learning algorithm DBSCAN. For star members
we build the radial density profiles, the spatial distributions and compute the
King parameters. The ages and metallicities were estimated using the BASE-9
Bayesian software. Results. We identified 958, 744 and 488 star members for the
Pleiades, Praesepe and Blanco 1 respectively. We corrected the distances and
built the spatial distributions, finding that Praesepe and Blanco 1 have
elongated shape structures. The distances, ages and metallicities obtained were
consistent with the reported in the literature. Conclusions. We obtained
catalogues of star members, updated kinematic and stellar parameters for these
open clusters. We found that the proper motions model can find a similar number
of members as the unsupervised clustering algorithm does when the cluster
population form an overdensity in the vector point diagram. It allows to select
an adequate size of the proper motions region to run these methods. Our
analysis found stars that are being directed towards the outskirts of the
Praesepe and Blanco 1, which exhibit elongated shapes.
