while the frequentist approach integrates on X , the Bayesian approach integrates on Θ. Say differently, the Bayesian approach uses the posterior distribution to integrate out the unknown quantity θ while the frequentist approach uses the likelihood to integrate out the known quantity x.
两种方法都是为了得出最似然的估计值，
从字面意识上来理解，frequentist参照的是X（x1，x2...），Bayesian参照的是θ（theta1,theta2,theta3）先验（原因），我觉得本质上两者没啥区别，
Frequentist decision rule: δ : X → D = δ(X)
Bayesian decision rule: δ : Θ → D = δ(Θ)
image.png
Posterior expected loss
The Bayesian approach considers the posterior expected loss
说实话，这个d是什么？
