Variable selection with error control: another look at stability selection

@article{Shah2011VariableSW,
  title={Variable selection with error control: another look at stability selection},
  author={Rajen Dinesh Shah and Richard J. Samworth},
  journal={Journal of The Royal Statistical Society Series B-statistical Methodology},
  year={2011},
  volume={75},
  pages={55-80}
}
  • Rajen Dinesh Shah, Richard J. Samworth
  • Published 2011
  • Mathematics
  • Journal of The Royal Statistical Society Series B-statistical Methodology
  • Summary. Stability selection was recently introduced by Meinshausen and Buhlmann as a very general technique designed to improve the performance of a variable selection algorithm. It is based on aggregating the results of applying a selection procedure to subsamples of the data. We introduce a variant, called complementary pairs stability selection, and derive bounds both on the expected number of variables included by complementary pairs stability selection that have low selection probability… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 36 REFERENCES

    Stability Selection

    VIEW 19 EXCERPTS
    HIGHLY INFLUENTIAL

    A stability index for feature selection

    VIEW 1 EXCERPT

    Ultrahigh Dimensional Feature Selection: Beyond The Linear Model

    VIEW 1 EXCERPT

    A Variance Reduction Framework for Stable Feature Selection

    • Yue Han, Lei Yu
    • Computer Science
    • 2010 IEEE International Conference on Data Mining
    • 2010
    VIEW 2 EXCERPTS

    Regression Shrinkage and Selection via the Lasso

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    Bolasso: model consistent Lasso estimation through the bootstrap

    VIEW 2 EXCERPTS