Bayesian Model Combination

Bayesian model combination (BMC) is an algorithmic correction to Bayesian model averaging (BMA). Instead of sampling each model in the ensemble individually, it samples from the space of possible ensembles (with model weights drawn randomly from a Dirichlet distribution having uniform parameters)

References

Ensemble learning. Wikipedia. Link.

Shultz, K. M., & Peterson, L. E. (2011). Model-averaged confidence intervals for ensemble learning. In International Joint Conference on Neural Networks (pp. 2677-2684). Link.