Using Empirical Bayes to approximate posteriors for large "black box" estimators
The Unofficial Google Data Science Blog
NOVEMBER 4, 2015
by OMKAR MURALIDHARAN Many machine learning applications have some kind of regression at their core, so understanding large-scale regression systems is important. Posteriors are useful to understand the system, measure accuracy, and make better decisions. Figure 4 shows the results of such a test.
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