In a recent colloquium, the speaker's abstract claimed they were using machine learning. During the talk, the only thing related to machine learning was that they perform linear regression on their data. After calculating the best-fit coefficients in 5D parameter space, they compared these coefficients in one system to the best-fit coefficients of other systems.
When is linear regression machine learning, as opposed to simply finding a best-fit line? (Was the researcher's abstract misleading?)
With all the attention machine learning has been garnering recently, it seems important to make such distinctions.
My question is like this one, except that that question asks for the definition of "linear regression", whereas mine asks when linear regression (which has a broad number of applications) may appropriately be called "machine learning".
I'm not asking when linear regression is the same as machine learning. As some have pointed out, a single algorithm does not constitute a field of study. I'm asking when it's correct to say that one is doing machine learning when the algorithm one is using is simply a linear regression.
All jokes aside (see comments), one of the reasons I ask this is because it is unethical to say that one is doing machine learning to add a few gold stars to your name if they aren't really doing machine learning. (Many scientists calculate some type of best-fit line for their work, but this does not mean that they are doing machine learning.) On the other hand, there are clearly situations when linear regression is being used as part of machine learning. I'm looking for experts to help me classify these situations. ;-)