Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent

Noah Simon, Jerome H. Friedman, Trevor Hastie, Rob Tibshirani

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We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of l1 and l2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a regularization path. We demonstrate the efficacy of our algorithm on real and simulated data sets, and find considerable speedup between our algorithm and competing methods.

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