The paper describes a method of the charged particle identification, developed for the mbox{CMD-3} detector, installed at the VEPP-2000 $e^{+}e^{-}$ collider. The method is based on the application of the boosted decision trees classifiers, trained for the optimal separation of electrons, muons, pions and kaons in the momentum range from 100 to $1200~{rm MeV}/c$. The input variables for the classifiers are linear combinations of the energy depositions of charged particles in 12 layers of the liquid xenon calorimeter of the mbox{CMD-3}. The event samples for training of the classifiers are taken from the simulation. Various issues of the detector response tuning in simulation and calibration of the calorimeter strip channels are considered. Application of the method is illustrated by the examples of separation of the $e^+e^-(gamma)$ and $pi^+pi^-(gamma)$ final states and of selection of the $K^+K^-$ final state at high energies.
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