l0ara: Sparse Generalized Linear Model with L0 Approximation for Feature Selection

An efficient procedure for feature selection for generalized linear models with L0 penalty, including linear, logistic, Poisson, gamma, inverse Gaussian regression. Adaptive ridge algorithms are used to fit the models.

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Package details

AuthorWenchuan Guo, Shujie Ma, Zhenqiu Liu
MaintainerWenchuan Guo <[email protected]>
Package repositoryView on CRAN
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l0ara documentation built on May 1, 2019, 8:02 p.m.