Formally it's a generalized linear model with a constructed feature set.
A "kitchen sink" regression with enough polynomial terms (x^2, x^3, etc.) and interaction terms (ab, (ab)^2, etc.) will be a function approximator the same way a neural net is.
The computational mechanics are different (there's a reason we dont use it) but in the land of infinite computational power it can be made equivalent.
A "kitchen sink" regression with enough polynomial terms (x^2, x^3, etc.) and interaction terms (ab, (ab)^2, etc.) will be a function approximator the same way a neural net is.
The computational mechanics are different (there's a reason we dont use it) but in the land of infinite computational power it can be made equivalent.