For many regression/classification algorithms, we have the bayesian version of it. Like bayesian linear regression, bayesian logistic regression, bayesian neuron network. I do not fully understand the math in them, but what are its advantages compared with the original algorithm? Is is of great practical use?

**Answer**

Doing Bayesian regression is not *an algorithm* but a different approach to statistical inference. The major advantage is that, by this Bayesian processing, you recover the whole range of inferential solutions, rather than a point estimate and a confidence interval as in classical regression. (I can only recommend you to read a statistics manual to understand the difference between an algorithm and statistical inference.)

**Attribution***Source : Link , Question Author : FindBoat , Answer Author : Xi’an*