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.

AuthorWenchuan Guo, Zhenqiu Liu, Fengzhu Sun, Dermot P McGovern, Sandra Orsulic
Date of publication2016-08-05 11:53:20
MaintainerWenchuan Guo <wguo007@ucr.edu>
LicenseGPL-2
Version0.1.3

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