Using random effects models in prediction problems
The Unofficial Google Data Science Blog
MARCH 31, 2016
In the context of prediction problems, another benefit is that the models produce an estimate of the uncertainty in their predictions: the predictive posterior distribution. both L1 and L2 penalties; see [8]) which were tuned for test set accuracy (log likelihood). ICML, (2005). [3] 2005): 301-320. [9] bandit problems).
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