Thanks for elaborating both questions. The classification question was about whether a multidimensional space of mixed discrete subspace and continuous subspace can construct a classification problem. Conceptually, I would say yes in that the models parametrized by the instance sets of both discrete subspace and continuous subspace could classify the data in the space if one observes predictors (discrete and continuous) and labels, p(y=c|x_discrete, x_continuous, theta_discrete, theta_continuous), like fixed mixture model except that here one involves discrete subspace additionally. Does it make sense? and is it possible to construct a probabilistic graph model to do it? Maybe, there is a more sensible/correct way in using PyMC3 to model this problem.
Thank you
Chris