Classification Method of Welding Defect Based on Generalized Weighted SVM

A classification algorithm of generalized weighted support vector machine(GWSVM) is put forward.In order to improve the class accuracy of small number of samples caused by the imbalance of sample number,weight of sample difference is introduced.According to experience,the importance weights of different classes is manually determined to solve the importance of different classes.The method of fuzzy cluster with superision is used to determine the weights of sample importance.Testing results show that GWSVM can improve the inspection accuracy of a small number of important defects when the noise and sample sort have important effect.