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
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;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
DOI :
10.1109/CSAE.2011.5953162