Relaxed Lasso

@article{Meinshausen2007RelaxedL,
  title={Relaxed Lasso},
  author={N. Meinshausen},
  journal={Comput. Stat. Data Anal.},
  year={2007},
  volume={52},
  pages={374-393}
}
  • N. Meinshausen
  • Published 2007
  • Computer Science
  • Comput. Stat. Data Anal.
  • The Lasso is an attractive regularisation method for high dimensional regression. It combines variable selection with an efficient computational procedure. However, the rate of convergence of the Lasso is slow for some sparse high dimensional data, where the number of predictor variables is growing fast with the number of observations. Moreover, many noise variables are selected if the estimator is chosen by cross-validation. It is shown that the contradicting demands of an efficient… CONTINUE READING
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