In Chapters 7 and 8, learning was divorced from reasoning. An alternative is to explicitly use probabilistic reasoning, as in Chapter 9, with data providing evidence that can be conditioned on. This provides a theoretical basis for much of machine learning, including regularization and measures of simplicity.
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