Title :
Research on noise insensitive SVM based multi-class classifier
Author :
Li, Kan ; Liu, Yu-shu
Author_Institution :
Dept. of Comput. Sci. & Eng., Beijing Inst. of Technol., China
Abstract :
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.
Keywords :
noise; pattern classification; support vector machines; data characteristics analysis; high dimension data set; multiclass classifier; noise insensitive SVM; one against one method; optimal separating hyperplane; Computer science; Cybernetics; Data analysis; Databases; Electronic mail; Gaussian processes; Information science; Machine learning; Support vector machine classification; Support vector machines;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1378593
