The website is in Maintenance mode. We are in the process of adding more features.
Any new bookmarks, comments, or user profiles made during this time will not be saved.

AIML.com

Machine Learning Resources

What are the main components of a Bayesian Model?

Bookmark this question

Adapted from Bayes’ Rule, the basic setup of Bayesian inference is:

where is the posterior, or the distribution of the parameter updated after observing data X. is the likelihood of the observed data

is the prior distribution assigned to based on a subjective degree of beliefP(X) is the marginal distribution of X that normalizes the posterior into a valid probability distribution

Leave your Comments and Suggestions below:

Please Login or Sign Up to leave a comment

Partner Ad  

Find out all the ways
that you can

Explore Questions by Topics