Bayesian Model Averaging(BMA) and Combining Models

Preliminaries Bayesian Theorem Bayesian Model Averaging(BMA)1 Bayesian model averaging(BMA) is another wildly used method that is very like a combining model. However, the difference between BMA and combining models is also significant. A Bayesian model averaging is a Bayesian formula in which the random variable are models(hypothesizes) h=1,2,,Hh=1,2,\cdots,H with prior probability Pr(h)\Pr(h), then the marginal distribution over data XX is: Pr(X)=h=1HPr(Xh)Pr(h) \Pr(X)=\sum_{h=1}^{H}\Pr(X|h)\Pr(h) And the MBA is used to select a model(hypothesis) that can model the data best through Bayesian theory....

March 7, 2020 · (Last Modification: April 28, 2022) · Anthony Tan