How does SVM perform in high-noise nonlinear datasets?

SVM struggles in high-noise nonlinear data but RBF kernels with proper tuning help.

Nonlinear noisy data requires flexible kernels like RBF. However, excessive noise leads to many support vectors, increasing complexity and reducing generalization. Proper C and gamma tuning is essential.