Why does Baldi use Bayesian inference in machine learning?
I employ Bayesian inference because it provides a rigorous and principled framework for dealing with uncertainty, which is inherent in all real-world data. By defining prior beliefs about model parameters and updating them with observed data through a likelihood function, Bayesian methods offer a way to quantify uncertainty in predictions and model complexity. This approach leads to more robust and interpretable learning systems. It allows us to express what we know before seeing the data and how to incorporate new information systematically.
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