Yet still limited compared to even not-very-deep NNs. If the user wants to fit a parabola with a linear regression, he pretty much has to manually add a quadratic term himself.
I think they’re widely used primarily because they’re widely taught in school.
Well, thanks to quantum mechanics; pretty much all of existence is probably “just statistics”.
Well, practically all interesting statistics are NONlinear regressions. Including ML. And your brain. And physics.
What a lot of people don’t understand is that linear regression can still handle non-linear relationships.
For a statistician, linear regression just means the coefficients are linear, it doesn’t mean the relationship itself is a straight line.
That’s why linear models are still incredibly powerful and are used so widely across so many fields.
Yet still limited compared to even not-very-deep NNs. If the user wants to fit a parabola with a linear regression, he pretty much has to manually add a quadratic term himself.
I think they’re widely used primarily because they’re widely taught in school.