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skglm 0.3.1 documentation
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skglm 0.3.1 documentation
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Stable Dev
  • Getting started
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    • Value and proximal operators of penalties
    • Comparison of Lasso and Weighted Lasso
    • Weighted Lasso with some zero weights
    • Logistic regression with Elastic net and minimax concave penalties
    • Timing comparison between direct prox computation and reweighting
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    • Sparse recovery with non-convex penalties
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    • skglm.GeneralizedLinearEstimator
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Tutorials#


How to add a custom datafit#

Learn to add a custom datafit through a hands-on examples: Implementing a Poisson datafit.

How to add a custom penalty#

Learn to add a custom penalty by implementing the `\ell_1` penalty.

Computation of the intercept#

Explore how skglm fits an unpenalized intercept.

Mathematics behind Cox datafit#

Get details about Cox datafit equations.

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On this page
  • Tutorials
    • How to add a custom datafit
    • How to add a custom penalty
    • Computation of the intercept
    • Mathematics behind Cox datafit