How does SVM avoid overfitting?

SVM avoids overfitting by maximizing margin and controlling complexity through regularization.

The margin maximization principle reduces model complexity, while parameter C controls tradeoff between margin size and training error. Kernel parameters like gamma also influence model flexibility.