Where is it best to use svm with linear kernel?

Question

I am currently studying SVM and was wondering what the application of SVM's with the linear kernel is. In my opinion, it must be something applied to solve a linear optimization problem. Is this correct?

I appreciate your answer!

Answer 1

The application of an SVM with a linear kernel is to deal with classification or regression tasks. It is preferred majorly if data can be separated by a linear decision boundary or a linear fit to the data, thus the linear kernel.

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