Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time Complexity Analysis"
2003
Conference Paper
ei
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
Author(s): | Shin, H. and Cho, S. |
Journal: | Lecture Notes in Computer Science (LNCS 2690) |
Volume: | LNCS 2690 |
Pages: | 1008-1015 |
Year: | 2003 |
Month: | September |
Day: | 0 |
Publisher: | Springer-Verlag |
Department(s): | Empirische Inferenz |
Bibtex Type: | Conference Paper (inproceedings) |
Event Name: | The 4th International Conference on Intelligent Data Engineering (IDEAL) |
Event Place: | Hong Kong, China |
Address: | Heidelberg |
Digital: | 0 |
Institution: | Seoul National University, Seoul, Korea |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
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BibTex @inproceedings{2694, title = {Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time Complexity Analysis"}, author = {Shin, H. and Cho, S.}, journal = {Lecture Notes in Computer Science (LNCS 2690)}, volume = {LNCS 2690}, pages = {1008-1015}, publisher = {Springer-Verlag}, organization = {Max-Planck-Gesellschaft}, institution = {Seoul National University, Seoul, Korea}, school = {Biologische Kybernetik}, address = {Heidelberg}, month = sep, year = {2003}, doi = {}, month_numeric = {9} } |