Multiclass SVMs

However, these are not very elegant approaches to solving multiclass problems. A better alternative is provided by the construction of multiclass SVMs, where we build a two-class classifier over a feature vector derived from the pair consisting of the input features and the class of the datum. At test time, the classifier chooses the class . The margin during training is the gap between this value for the correct class and for the nearest other class, and so the quadratic program formulation will require that . This general method can be extended to give a multiclass formulation of various kinds of linear classifiers.