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Proceedings Paper

A new incremental learning algorithm based on Support Vector Machines
Author(s): Zuying Miao; Nong Sang
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Paper Abstract

In this paper, we first analyzed the possible change of support vector set after new samples are added, then presented a new support vector machine incremental learning algorithm. This algorithm reconstructed SVM classifier through the selection of training samples in incremental learning based on change regularity of support vectors after new samples are added. Finally, the algorithm has a higher classification accuracy than traditional SVM incremental algorithms through experimental verification.

Paper Details

Date Published: 30 October 2009
PDF: 6 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 749615 (30 October 2009); doi: 10.1117/12.832552
Show Author Affiliations
Zuying Miao, Huazhong Univ. of Science and Technology (China)
South-Central Univ. for Nationalities (China)
Nong Sang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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