Fast multi-class support vector machine

A binary encoding based fast multi-class support vector machine (SVM) is introduced. How to avoid the uneven class size of each SVM in the multi-classification system is discussed based on the encoding method. Then the strategy of searching the optimal division of different classes is proposed. Thus, with little loss of accuracy the system has a higher classification speed than the traditional ones. Therefore, the classifier is suitable for real time or online systems. Finally, the introduced classification system is evaluated by experiments.