Regularization Paths for Generalized Linear Models via Coordinate Descent.

@article{Friedman2010RegularizationPF,
  title={Regularization Paths for Generalized Linear Models via Coordinate Descent.},
  author={J. Friedman and T. Hastie and R. Tibshirani},
  journal={Journal of statistical software},
  year={2010},
  volume={33 1},
  pages={
          1-22
        }
}
  • J. Friedman, T. Hastie, R. Tibshirani
  • Published 2010
  • Computer Science, Medicine
  • Journal of statistical software
  • We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include ℓ(1) (the lasso), ℓ(2) (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In… CONTINUE READING
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    References

    SHOWING 1-10 OF 78 REFERENCES
    L 1-regularization path algorithm for generalized linear models
    • 153
    • PDF
    L1‐regularization path algorithm for generalized linear models
    • 562
    • PDF
    Sparse inverse covariance estimation with the graphical lasso.
    • 3,848
    • PDF
    Sparse multinomial logistic regression: fast algorithms and generalization bounds
    • 860
    • Highly Influential
    • PDF
    Piecewise linear regularized solution paths
    • 454
    • PDF
    Coordinate descent algorithms for lasso penalized regression
    • 678
    • PDF
    An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
    • 634
    • PDF
    Regression Shrinkage and Selection via the Lasso
    • 30,790
    • PDF
    Fast sparse regression and classification
    • 193
    PATHWISE COORDINATE OPTIMIZATION
    • 1,767
    • PDF