My goal is to understand the advantages of Support Vector Machine. What I have in mind is that Support Vector Machine can have kernel Radial Basis Function ie
SVR(kernel='rbf'), which is a infinite dimension (X1 as x-axis, y as y-axis, X2 as z-axis, X3 as a-axis, X4 as b-axis, and so on).
The problem is StatQuest video showed that Linear Regression can do 3 axis as well.
I am so confused.