STRUCTURE OF A MODEL WITH HIDDEN VARIABLES, METHOD FOR PRODUCING AN INFERENCE FOR SAID MODEL AND METHOD FOR LEARNING THE PARAMETERS FROM DATA FROM SAID MODEL

摘要

The invention relates to a data generating structure for a model with hidden variables corresponding to a causal network, wherein the arrows of hidden source variables point to the observed variables. According to the invention, said structure directly allocates continuously observed variables to binary hidden sources.