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I'm trying to follow this tutorial on Bayesian Model Averaging by putting it in context of machine-learning and the notations that it generally uses (i.e.): X_train Bayesian Model Averaging (BMA) is a technique for amalgamating several plausible probability models fit to the same data set using Bayes Theorem.

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Abstract: Bayesian Model Averaging (BMA) is an application of Bayesian inference to the problems of model selection, combined estimation and prediction that produces Draft MrBayes version 3.2 Manual: Tutorials and Model Summaries Fredrik Ronquist, improve convergence, and facilitate Bayesian model averaging and model choice.

Improving Predictions Using Ensemble Bayesian Model Averaging Jacob M. Montgomery Department of Political Science Washington University in St. Louis CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda):

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