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A Fast MultiClass Support Vector Machine |
LI JianWu, LU Yao |
School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081 |
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Abstract A binary encoding based fast multiclass support vector machine(SVM) is introduced. How to avoid the uneven class size of each SVM in the multiclassification 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.
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Received: 19 June 2006
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