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The weighted maximum vector angular margin core vector machinefor imbalanced data classification

LU Shuxia, LI Limin   

  1. College of Mathematics and Computer Science, Hebei University, Baoding 071002, Hebei, China
  • Received:2013-06-28 Online:2014-06-20 Published:2013-06-28

Abstract: A new classification approach was proposed in order to deal with large size and imbalanced datasets classification problem. The proposed method was based on the maximum vector angular margin core vector machine to implement classification for large datasets. For the imbalanced datasets classification problem, each sample was assigned by different weights, which could improve the classification performance of algorithm. The proposed approach could effectively solve the imbalanced datasets classification problem and implement fast training on large datasets.

Key words: the maximum vector angular margin, the minimum enclosing ball, weight, core vector machine, imbalanced data, the core set

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