Among the following approaches, which one can NOT extend the linear SVM to non$-$linear SVM$?$

Given a linear Support Vector Machine as follows:

Among the following approaches, which one can NOT extend the linear SVM to non$-$linear SVM$?$

Introduce the quadratic and cubic terms of the original features.

Introduce interaction terms among the original data features.

Use Radial Kernel $($Radial Base Function$)$ to define the non$-$linear relationship among data instances.

Double the length of $.$