Regularization Paths for Generalized Linear Models via Coordinate Descent

Friedman, Jerome H.; Hastie, Trevor; Tibshirani, Rob

Regularization Paths for Generalized Linear Models via Coordinate Descent

Jerome H. Friedman, Trevor Hastie and Rob Tibshirani

Journal of Statistical Software, 2010, vol. 033, issue i01

Abstract: We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso), ℓ2 (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 comparative timings we find that the new algorithms are considerably faster than competing methods.

Date: 2010-02-02
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:033:i01

DOI: 10.18637/jss.v033.i01

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