A novel pattern recognition algorithm: Combining ART network with SVM to reconstruct a multi-class classifier

作者：Wang Anna; Yuan Wenjing; Liu Junfang; Yu Zhiguo; Li Hua

来源：Computers & Mathematics with Applications, 2009, 57(11-12): 1908-1914.

DOI：10.1016/j.camwa.2008.10.052

• ART network
• Fault diagnosis
• One-against-one
• Multiclassification
• SVM

Based on the principle of one-against-one support vector machines (SVMs) multi-class classification algorithm, this paper proposes an extended SVMs method which couples adaptive resonance theory (ART) network to reconstruct a multi-class classifier. Different coupling strategies to reconstruct a multi-class classifier from binary SVM classifiers are compared with application to fault diagnosis of transmission line. Majority voting, a mixture matrix and self-organizing map (SOM) network are compared in reconstructing the global classification decision. In order to evaluate the method's efficiency, one-against-all, decision directed acyclic graph (DDAG) and decision-tree (DT) algorithm based SVM are compared too. The comparison is done with Simulations and the best method is validated with experimental data.

• 出版日期2009-6
• 单位东北大学