APML0: Augmented and Penalized Minimization Method L0
Fit linear, logistic and Cox models regularized with L0, lasso
(L1), elastic-net (L1 and L2), or net (L1 and Laplacian) penalty, and
their adaptive forms, such as adaptive lasso / elastic-net and net
adjusting for signs of linked coefficients. It solves the L0 penalty
problem by simultaneously selecting regularization parameters and
performing hard-thresholding or selecting the number of non-zeros. This
augmented and penalized minimization method provides an approximation
solution to the L0 penalty problem, but runs as fast as L1 regularization.
The package uses a one-step coordinate descent algorithm and runs extremely
fast by taking into account the sparsity structure of coefficients. It can
handle very high dimensional data and has superior selection performance.
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