Question

Why svm is a good option for high dimensional data?

Answer 1

Answer:

As others pointed out already, you are facing a typical P≫N situation, where the number of predictors, i.e., features, is much greater than the number of instances. In this situation, SVM is generally a good choice, as its maximum margin property gives some guarantees on the generalization performance

Answer 2

Answer:

Yes

Explanation:

SVM is a good option for high dimensinal because it helps in guarantees in the generalization performance.