| w • x| ≥ γ, ∀ x ∈ X (training set), the error of c is bounded by b/ + k R 2 γ 2 log 2 + log 1 δ with a probability 1 − δ, where = |X | and b is the number of examples with margin less than γ.
if X is separated with a margin γ by a linear classifier, then the error has a bound depending on γ.