How does SVM perform feature selection implicitly?

SVM implicitly selects features by assigning zero or low weights to irrelevant dimensions.

In linear SVM, weight vector magnitudes indicate feature importance. Features with near-zero weights contribute little to decision boundary, effectively performing implicit feature selection.