DocumentCode
547401
Title
An incremental algorithm of support vector machine based on distance ratio and k nearest neighbor
Author
Bing-xiang, Liu ; Xiang, Cheng
Author_Institution
Sch. of Inf. Eng., JDZ Ceramic Inst., Jingdezhen, China
Volume
1
fYear
2011
fDate
10-12 June 2011
Firstpage
18
Lastpage
20
Abstract
For large data sets and data updated situation, incremental training algorithm is an effective solution of support vector machine training. To improve speed of incremental support vector machine training algorithm, this paper combines the distance ratio method and the nearest neighbor method to extract boundary samples, and an incremental support vector machine algorithm based on distance ratio and k nearest neighbor was proposed, this algorithm can eliminate useless samples as far as possible, thus reduces the training time at remaining essentially the same training accuracy.
Keywords
learning (artificial intelligence); support vector machines; very large databases; data updated situation; distance ratio; incremental algorithm; incremental training algorithm; k nearest neighbor algorithm; large data sets; support vector machine training; Accuracy; Classification algorithms; Statistical learning; Support vector machine classification; Training; distance ratio; incremental; k nearest neighbor; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-8727-1
Type
conf
DOI
10.1109/CSAE.2011.5953162
Filename
5953162
Link To Document