Hinge Loss

In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for “maximum-margin” classification, most notably for support vector machines (SVMs).

For an intended output t = ±1 and a classifier score y, the hinge loss of the prediction y is defined as

$\ell (y)=\max (0,1-t\cdot y)$