Multi-view twin support vector machines

@article{Xie2015MultiviewTS,
  title={Multi-view twin support vector machines},
  author={Xijiong Xie and Shiliang Sun},
  journal={Intell. Data Anal.},
  year={2015},
  volume={19},
  pages={701-712}
}
Twin support vector machines are a recently proposed learning method for binary classification. They learn two hyperplanes rather than one as in conventional support vector machines and often bring performance improvements. Multiview learning is concerned about learning from multiple distinct feature sets, which aims to exploit distinct views to improve generalization performance. In this paper, we propose multi-view twin support vector machines by solving a pair of quadratic programming… CONTINUE READING

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