Title :
Pre-extracting support vector by adaptive projective algorithm
Author :
Ai-ling, Ding ; Fang, Liu ; Ying Li
Author_Institution :
Comput. Sch., Xidian Univ., Xi´´an, China
Abstract :
A new method, called adaptive projective algorithm, which is able to extract support vectors from given training examples, is put forward as a support vector algorithm. The method greatly reduces the training samples and so improves the speed of the support vector machine, while the ability of the support vector machine in pattern classification is unaffected: Our experimental results show remarkable improvement of speed to support our idea.
Keywords :
adaptive signal processing; iterative methods; learning (artificial intelligence); learning automata; optimisation; pattern classification; adaptive projective algorithm; iterative method; optimization; pattern classification; support vector algorithm; support vector machine; training examples; Data mining; Erbium; Iterative algorithms; Iterative methods; Pattern classification; Risk management; Support vector machine classification; Support vector machines; Training data; Upper bound;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1180973