The hybrid tree model then focuses on the learning of these model parameters from the training data using maximum likelihood estimation.
the model tries to maximize: Since the correct hybrid tree associated with n-m pair is unknown, we marginalize over the hidden variable h. The model parameters will then be estimated using the Expectation-Maximization (EM) algorithm (Dempster et al., 1977).