（1.4）贝叶斯规则

AI100 2023-01-12 23:11:08

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（1.4）贝叶斯规则

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Over a number of years I taught the standard, classical, theory of statistics to a large number of students, most of whom appeared to have similar difficulties to those I had myself encountered in understanding the nature of the conclusions that this theory comes to. However, the mere fact that students have difficulty with a theory does not prove it wrong. More importantly, I found the theory did not improve with better acquaintance, and I went on studying Bayesian theory. It turned out that there were real differences in the conclusions arrived at by classical and Bayesian statisticians, and so the former was not just a special case of the latter corresponding to a conventional choice of prior beliefs. On the contrary, there was a strong disagreement between statisticians as to the conclusions to be arrived at in certain standard situations, of which I will cite three examples for now.

Bayesian Methods for Statistical Analysis，统计分析中的贝叶斯方法（2015年书籍）

人工智能之不确定知识表示及推理.pptx

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