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ICNC
2005
Springer

Support Vector Based Prototype Selection Method for Nearest Neighbor Rules

9 years 1 months ago
Support Vector Based Prototype Selection Method for Nearest Neighbor Rules
The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimization, so they have good generalization ability. We proposed a new prototype selection method based on support vectors for nearest neighbor rules. It selects prototypes only from support vectors. During classification, for unknown example, it can be classified into the same class as the nearest neighbor in feature space among all the prototypes. Computational results show that our method can obtain higher reduction rate and accuracy than popular condensing or editing instance reduction method.
Yuangui Li, Zhonghui Hu, Yunze Cai, Weidong Zhang
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICNC
Authors Yuangui Li, Zhonghui Hu, Yunze Cai, Weidong Zhang
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