Understanding the Theory of Bayesian Regression

Bayesian regression

Bayesian theory is a probabilistic approach to statistical inference and is widely used in machine learning for various tasks, including regression. Bayesian regression involves modeling a relationship between a response variable and one or more predictor variables while considering the uncertainty in the model parameters.

Mathematical foundation

In Bayesian regression, the goal is to infer the posterior distribution of the model parameters given the observed data. Bayes’ theorem gives the posterior distribution: