主题:开个头:读《The Book of Why》的笔记和讨论 -- 鸿乾

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2018-09-15 14:44:33
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鸿乾鸿乾`84333`/bbsIMG/face/0000.gif`70`391`1700`14318`正六品上:朝议郎|昭武校尉`2012-04-02 07:53:45`
一些相关链接 7

我本来希望这个讨论放在科技天地里面,我也是在那里发帖的。但是不知为何放在了新兵这里。因此,一直没有看见。直到查了站内信箱,才知道发在这里。

两个知乎里面的相关链接:

从相关性到因果性

从这个文章知道,这本书在国内似乎也很热门。

【综述长文】因果关系是什么?结构因果模型入门

这个文章很长。

纽约时报的评论

下面是Amazon的一位读者的评论:

The Book of Why is a popular introduction to Judea Pearl’s branch of causal inference. But it is also so much more.

Pearl has written many other textbooks introducing his graphical approach. But in this book, Pearl provides an engaging narrative of the history of causal inference, the important distinctions he sees in his branch and its importance for the future of Artificial Intelligence.

Briefly, Pearl views classical statistics as seriously flawed in not having developed a meaningful theory of causality. While able to demonstrate correlation, Pearl asserts that in classical statistics all relationships are two-way: that is 2x=3y+6 can also be written 3y=2x-6. We are left in doubt as to whether x causes y or y causes x.

Fundamentally, Pearl sees this problem as still plaguing all artificial intelligence and statistics. In its place, Pearl argues that the exact causal relationship between all variables should be explicitly symbolized in graphical form and only then can mathematical operations tease out the precise causal effect.

To be transparent, I am trained in the Rubin approach to causal inference and disagree with some of Pearl’s history and characterization of statistics. But that is not the point. The history is well-written, engaging and understandable by the lay reader. Similarly, his account of graphical causal inference theory is followable even for someone like myself who did not learn these techniques in graduate school.

以这些作为开始吧。总之,是想说,书值得仔细读读。希望看到更多的河友的参与。


通宝推:胡一刀,
2018-09-15 14:44:33

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