Bayesian Oracle 神谕·贝叶斯

Bayes' Theorem / 贝叶斯定理： Start with prior beliefs about each hypothesis. When you see evidence E, multiply each prior by the likelihood P(E|H) — how likely that evidence would be if the hypothesis were true. Normalize by P(E) (the total probability of seeing E across all hypotheses) to get the posterior.
从每个假设的先验信念开始。当你看到证据 E 时，将每个先验乘以似然 P(E|H)——即如果假设成立，看到该证据的概率。再除以 P(E)（在所有假设下看到 E 的总概率）进行归一化，得到后验。