I read some chapters of a book called "Black Swan"by "Nassim Taleb". In the book events in the world are categorized as mediocre/extreme. In mediocre stand you don't need to worry about an anomaly with big effect on the results in the data but in extreme stand we may after a long period of time and in very rare situations run into an event with very large influence(Black Swan) that is not considered to be observed in the data in advance.
I want to know what are the major criteria for some data to be considered from the mediocre or extreme stands in the machine learning.
I presume it is wrong to use machine learning for extreme stand view events because a single data can have extreme effect and question our findings.
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