A neural network approach to ordinal regression

@article{Cheng2008ANN,
  title={A neural network approach to ordinal regression},
  author={J. Cheng and Zheng Wang and G. Pollastri},
  journal={2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={1279-1284}
}
  • J. Cheng, Zheng Wang, G. Pollastri
  • Published 2008
  • Computer Science, Mathematics
  • 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)
Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional neural network to learn ordinal categories. Our approach is a generalization of the perceptron method for ordinal regression. On several benchmark datasets, our method (NNRank) outperforms a neural network classification method. Compared with the ordinal regression methods using Gaussian processes and support vector… Expand
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