Least angle and ℓ 1 penalized regression: A review

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Abstract

Least Angle Regression is a promising technique for variable selection applications, offering a nice alternative to stepwise regression. It provides an explanation for the similar behavior of LASSO ℓ 1 -penalized regression) and forward stagewise regression, and provides a fast imple- mentation of both. The idea has caught on rapidly, and sparked a great deal of research interest. In this paper, we give an overview of Least Angle Regression and the current state of related research.

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Hesterberg, T., Choi, N. H., Meier, L., & Fraley, C. (2008). Least angle and ℓ 1 penalized regression: A review. Statistics Surveys, 2, 61–93. https://doi.org/10.1214/08-SS035

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