The theory of SVM for a two class problem could be found in many
references [26,29] (Fig. 1). Traditional SVM only provides two-class
classification algorithm, and it is important to extend it to multiclass
classification cases. There are already some multi-class SVM
strategies that were put forward before and have become comparatively
mature. In general these methods can be grouped into two
types: one is constructing and combing several binary class classifiers,
and the other is considering all data in one optimization formulation
directly [13]. Four popular methods, including 1-against-1 (1-a-1), 1-
against-all (1-a-a), decision directed acyclic graph (DDAG) and binary
tree (BT), are introduced as follows.