Title :
A novel incremental SVM learning algorithm
Author :
Wenhua, Zeng ; Jian, Ma
Author_Institution :
Dept. of Comput. Sci., Xiamen Univ., China
Abstract :
In this paper we present a novel approach to incremental support vector machine (SVM) learning algorithm. We analyze the possible change of support vector set after new samples are added to training set. Based on the analysis result, a novel algorithm is presented. In this algorithm useless samples are discarded and knowledge is accumulated. The experiment result shows that this algorithm is more effective than traditional SVM while the classification precision is also guaranteed.
Keywords :
learning (artificial intelligence); support vector machines; SVM classification; incremental SVM learning algorithm; machine learning; support vector machine; Algorithm design and analysis; Computer science; Educational institutions; Kernel; Machine learning; Machine learning algorithms; Neural networks; Statistical learning; Support vector machine classification; Support vector machines;
Conference_Titel :
Computer Supported Cooperative Work in Design, 2004. Proceedings. The 8th International Conference on
Print_ISBN :
0-7803-7941-1
DOI :
10.1109/CACWD.2004.1349105
