How does SVM behave in presence of correlated noise features?

SVM is robust but correlated noise can distort decision boundaries.

Correlated noisy features increase dimensional redundancy and can lead to unstable hyperplanes in linear SVM. Kernel methods may amplify noise if not regularized properly.