1. ALGORITHM OF ε-SVR BASED ON A LARGE-SCALE SAMPLE SET:: STEP-BY-STEP SEARCH.
- Author
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ZENG, SHAOHUA, TANG, Y. Y., WEI, YAN, and WANG, YONG
- Subjects
- *
ALGORITHMS , *SUPPORT vector machines , *STOCHASTIC convergence , *SEARCH algorithms , *SIMULATION methods & models , *STATISTICAL sampling , *ALGEBRA , *MATHEMATICAL analysis - Abstract
In view of the support vectors of ε-SVR that are not distributed in the ε belt and only located on the outskirts of the ε belt, a novel algorithm to construct ε-SVR of a large-scale training sample set is proposed in this paper. It computes firstly the ε-SVR hyper-plane of a small training sample set and the distances d of all samples to the hyper-plane, then deletes the samples not in field ε ≤ d ≤ dmax and searches SVs gradually in the scope ε ≤ d ≤ dmax, and trains step-by-step the final ε-SVR. Finally, it analyzes the time complexity of the algorithm, and verifies its convergence in the theory and tests its efficiency by the simulation. [ABSTRACT FROM AUTHOR]
- Published
- 2011
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