Research on noise insensitive SVM based multi-class classifier

A noise insensitive SVM multi-class classifier is proposed. The algorithm is used to analyze data characteristic in the high-dimension data set. Firstly a noise insensitive SVM two-class classifier is built to tackle the noise problem. On the basis of standard SVM, constraint distance is also considered to determine the optimal separating hyperplane. According to these, the noise insensitive SVM multi-class classifier is designed with edited SVM, confidence interval and one-against-one method.