A novel support vector machine with its features weighted by mutual information

@article{Xing2008ANS,
  title={A novel support vector machine with its features weighted by mutual information},
  author={Hong-Jie Xing and Minghu Ha and Da-Zeng Tian and Bao-Gang Hu},
  journal={2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={315-320}
}
A novel support vector machine (SVM) with weighted features is proposed. To assign appropriate weights for each feature, a mutual information (MI) based approach is presented. Although the calculation of feature weights may add an extra computational cost, the proposed method generally exhibits better generalization performance over the traditional SVM. The numerical studies on one synthetic and five existing benchmark classification problems confirm the benefits in using the proposed method. 
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