Network fault diagnosis based on rough set-support vector machine
Guo Jiang-wei, Xiaoping Wu, Qing Ye · 2010
At present, the technique of network fault diagnosis has been a very hot research domain. The scholars from both domestic and abroad have put forward many diagnosis approaches, but many of which have some disadvantages in dealing with uncertain problems. This paper proposes a rough set-support vector machine algorithm after studying the rough set and the support vector machine theories. In order to reduce the dimensions of the classification space, the algorithm first diminishes the attributes of the faults by means of the rough set theory (RST), thus improves the effect of the classification of the support vector machine (SVM).