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TaXxER t1_j00kcrd wrote

Reply to comment by new_name_who_dis_ in [Discussion] Amazon's AutoML vs. open source statistical methods by fedegarzar

When I hear “classical methods” I associate that with traditional statistical methods that often aren’t even considered ML.

Note that frequentist stats also go by the name of classical methods (as opposed to Bayesian methods).

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Delta-tau t1_j01aysc wrote

In statistics jargon, classical methods are all frequentist inference methods which rely on asymptotic theory and p-values. Some of them, like linear regression, logistic regression, or ARMA models are nowadays viewed as ML. I guess the "ML" label is a bit vague and changes over time.

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TaXxER t1_j01xpkt wrote

Yeah I’m aware that linear and logistic regression are classical methods and are in the weird spot where they sometimes are and sometimes are not regarded as ML.

My comment was mostly aimed to argue against this claim in the comment that I replied to:

> Classic AI methods usually refers to non-statistical methods

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xgboostftw t1_j02ifkc wrote

I think the terminology is more common in the forecasting niche where (especially since the M4, M5 competitions) they started to separate out tree and NN architectures into "ML" and all other methods used for last 50 years are deemed "classical".

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Delta-tau t1_j02rk0k wrote

Yeah I guess "classical" can mean different things depending on the context.

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new_name_who_dis_ t1_j021jgc wrote

I have the same association as you if I hear classic (ML) methods. But not classic (AI) methods, those I associate with good old fashioned AI, which aren't statistical.

Maybe it's just me, idk. I studied AI in philosophy long before I took an ML class. And I took my first intro to ML class before they were teaching deep learning in intro to ML classes (though i missed this cut-off only by a year or two haha).

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