## November 16, 2020

# Uncertainty evaluation - a comparison of different approaches

After showing two (frequentist) ways of calculating prediction uncerainty, I wanted to see how they compare to each other, and Baysian approach. But how do you evaluate predicted distributions against single true values? And how do you evaluate the uncertainty itself? In this blog, I would like to compare three different methods, trained on a (slightly) more real-life dataset (boston house-prices [3]) by showing a metric used to evaluate single point predictions, and some plots to evaluate the uncertainty.
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