8.2 Bioinformatics and healthcare applicationsīayesian inference derives the posterior probability as a consequence of two antecedents: a prior probability and a " likelihood function" derived from a statistical model for the observed data.6 In frequentist statistics and decision theory.4.5 Estimates of parameters and predictions.3 Inference over exclusive and exhaustive possibilities The Variable Precision Rough Set (VPRS) model extends the basic rough set theory to incorporate probabilistic information.2 Formal description of Bayesian inference.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |