Individualized Multidirectional Variable Selection

@article{Tang2020IndividualizedMV,
  title={Individualized Multidirectional Variable Selection},
  author={Xiwei Tang and Fei Xue and Annie Qu},
  journal={Journal of the American Statistical Association},
  year={2020},
  volume={116},
  pages={1280 - 1296}
}
  • Xiwei Tang, F. Xue, A. Qu
  • Published 15 September 2017
  • Computer Science
  • Journal of the American Statistical Association
ABSTRACT In this article, we propose a heterogeneous modeling framework which achieves individual-wise feature selection and heterogeneous covariates’ effects subgrouping simultaneously. In contrast to conventional model selection approaches, the new approach constructs a separation penalty with multidirectional shrinkages, which facilitates individualized modeling to distinguish strong signals from noisy ones and selects different relevant variables for different individuals. Meanwhile, the… 

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