Causal discovery means finding causal relationship from observed data, but in many cases, the causal relationship cannot be simply determined according to the sequence of events. For example, the decline of the mercury column of the barometer is related to the increase of the probability of rain, and the decline of the mercury column is earlier than the rain, but the fact is that there is no causal relationship between the two. The correlation between them is that the decline of the mercury column and the rain are caused by the decrease of the atmospheric pressure at the same time.
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LinksNational Tibetan Plateau Data Center