# Likelihood Principle

tags
§machine_learning

Given a generative model for data $$d$$ given parameters $$\mathrm{\theta}$$, $$P(d|\mathrm{\theta})$$, and having observed a particular outcome $$d_1$$, all inferences and predictions should depend only on the function $$P(d_1 | \mathrm{\theta})$$.

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