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.



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