Corpus ID: 211010608

On the Consistency of Optimal Bayesian Feature Selection in the Presence of Correlations

@article{Foroughipour2020OnTC,
  title={On the Consistency of Optimal Bayesian Feature Selection in the Presence of Correlations},
  author={Ali Foroughi pour and Lori A. Dalton},
  journal={ArXiv},
  year={2020},
  volume={abs/2002.00120}
}
Optimal Bayesian feature selection (OBFS) is a multivariate supervised screening method designed from the ground up for biomarker discovery. In this work, we prove that Gaussian OBFS is strongly consistent under mild conditions, and provide rates of convergence for key posteriors in the framework. These results are of enormous importance, since they identify precisely what features are selected by OBFS asymptotically, characterize the relative rates of convergence for posteriors on different… Expand

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