Deep-gKnock: nonlinear group-feature selection with deep neural network

@article{Zhu2021DeepgKnockNG,
  title={Deep-gKnock: nonlinear group-feature selection with deep neural network},
  author={Guangyu Zhu and Tingting Zhao},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2021},
  volume={135},
  pages={
          139-147
        }
}
  • G. Zhu, Tingting Zhao
  • Published 2021
  • Computer Science, Mathematics, Medicine
  • Neural networks : the official journal of the International Neural Network Society
Feature selection is central to contemporary high-dimensional data analysis. Group structure among features arises naturally in various scientific problems. Many methods have been proposed to incorporate the group structure information into feature selection. However, these methods are normally restricted to a linear regression setting. To relax the linear constraint, we design a new Deep Neural Network (DNN) architecture and integrating it with the recently proposed knockoff technique to… Expand
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