  Multi-nucleon transfer reaction between 136Xe beam and 198Pt target was
performed using the VAMOS++ spectrometer at GANIL to study the structure of
n-rich nuclei around N=126. Unambiguous charge state identification was
obtained by combining two supervised machine learning methods, deep neural
network (DNN) and positional correction using a gradient-boosting decision tree
(GBDT). The new method reduced the complexity of the kinetic energy calibration
and outperformed the conventional method, improving the charge state resolution
by 8%
