A New Incremental Support Vector Machine Algorithm

Fengqing Han, Hongmei Li, Cheng Wen, Wenjuan Zhao


Support vector machine is a popular method in machine learning. Incremental support vector machine algorithm is ideal selection in the face of large learning data set. In this paper a new incremental support vector machine learning algorithm is proposed to improve efficiency of large scale data processing. The model of this incremental learning algorithm is similar to the standard support vector machine. The goal concept is updated by incremental learning. Each training procedure only includes new training data. The time complexity is independent of whole training set. Compared with the other incremental version, the training speed of this approach is improved and the change of hyperplane is reduced.


DOI: http://dx.doi.org/10.11591/telkomnika.v10i6.1445 

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