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,cdots,H) with prior probability (Pr(h)), then the marginal distribution over data (X) is:
[ 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.