Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time 
Complexity Analysis"

Shin, H; Cho, S

doi:10.1007/978-3-540-45080-1_142

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Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time Complexity Analysis"

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Shin, H., & Cho, S. (2003). Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time Complexity Analysis". In J. Liu, Y.-M. Cheung, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning: 4th International Conference, IDEAL 2003, Hong Kong, China, March 21-23, 2003 (pp. 1008-1015). Berlin, Germany: Springer.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-DBB3-9

Abstract

Training SVM requires large memory and long cpu time when the pattern set is large. To alleviate the computational burden in SVM training, we propose a fast preprocessing algorithm which selects only the patterns near the decision boundary. The time complexity of the proposed algorithm is much smaller than that of the naive M^2 algorithm