yes.... and? :)
All datasets have outliers. And your production data will always feature outliers of a kind never seen in your training data.
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My interpretation of this is: How your model performs on your test data will only apply to your production data to a degree.
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What are your favourite techniques to eliminate outliers ?
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Just delete them
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as a matter of fact, I am looking at few at present.
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When humans try to learn, for some reason, they often start with and even focus on outliers.
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Outliers are called outliers boz they are few. True intelligence is not only about how to deal with the majority, but also about how to deal with those few
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I think about this topic all the time. Very few systems have a true understanding of anything: most systems just use a bunch of heuristics which gets enough right that it is useful, but is not understanding. Real understanding includes the categorization of outliers.
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Does anyone know if the hysterical french relaxed with his covid 19 hysteria?
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