Support vector machine and its application in the classification of missing data

被引：0

作者：

Sun Xi-jing ^{[1
]}

Si Shou-kui ^{[1
]}

Liu Chao ^{[1
]}

机构：

[1] Naval Aeronaut Engn Acad, Dept Basic Sci, Yantai 264001, Peoples R China

来源：

2006 CHINESE CONTROL CONFERENCE, VOLS 1-5 | 2006年

关键词：

optimization hyperplane; Lagrange dual; C-SVM; serial minimization method; interpolation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：174 / +

页数：2