“…CPTs, which are marginal probability distributions, are often parameterized and calculated using approaches based on Monte Carlo simulation (Phan et al, 2016), Gibbs sampling or dynamic discretization (Nojavan, Qian, & Stow, 2017;Pérez-Miñana, 2016), maximum likelihood or the Laplace correction (Aguilera et al, 2011), or the expectation maximization algorithm for small and incomplete datasets and the gradient learning algorithm for large incomplete datasets and continuous data (McDonald et al, 2015). CPTs, which are marginal probability distributions, are often parameterized and calculated using approaches based on Monte Carlo simulation (Phan et al, 2016), Gibbs sampling or dynamic discretization (Nojavan, Qian, & Stow, 2017;Pérez-Miñana, 2016), maximum likelihood or the Laplace correction (Aguilera et al, 2011), or the expectation maximization algorithm for small and incomplete datasets and the gradient learning algorithm for large incomplete datasets and continuous data (McDonald et al, 2015).…”