Title :
Support Vector Machine and Its Application in the Classification of Missing Data
Author :
Sun Xi-jing ; Si Shou-kui ; Liu Chao
Author_Institution :
Dept. of Basic Sci., Naval Aeronaut. Eng. Acad., Yantai, China
Abstract :
Support vector machine (SVM) is a popular technique for classification. C-SVM is applied in the classification for the unknown samples, especially for the missing data samples. First serial minimization method is used to delete the characters which are independent on the outputs, correspondingly the data for these characters in primitive training samples is deleted and the classification function is recomputed. Otherwise the missing data is estimated by interpolation.
Keywords :
minimisation; pattern classification; support vector machines; C-SVM; Lagrange dual; hyperplane optimization; missing data classification; serial minimization; support vector machine; Aerospace engineering; Chaos; Electronic mail; Interpolation; Lagrangian functions; Minimization methods; Optimization methods; Sun; Support vector machine classification; Support vector machines; C-SVM; Lagrange dual; interpolation; optimization hyperplane; serial minimization method;
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
DOI :
10.1109/CHICC.2006.280529
