Tutorial 4: Introduction to Bayesian Decision Theory & Cost Functions
This tutorial focuses on Bayesian Decision Theory, which combines the posterior with cost functions that allow us to quantify the potential impact of making a decision or choosing an action based on that posterior. Cost functions are therefore critical for turning probabilities into actions!
- Implement three commonly-used cost functions: mean-squared error, absolute error, and zero-one loss
- Discover the concept of expected loss
- Choose optimal locations on the posterior that minimize these cost functions
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