R-universe search: topic:sparse-regression

Showing 3 of total 3 results (show query)

jolars

SLOPE:Sorted L1 Penalized Estimation

Efficient implementations for Sorted L-One Penalized Estimation (SLOPE): generalized linear models regularized with the sorted L1-norm (Bogdan et al. 2015). Supported models include ordinary least-squares regression, binomial regression, multinomial regression, and Poisson regression. Both dense and sparse predictor matrices are supported. In addition, the package features predictor screening rules that enable fast and efficient solutions to high-dimensional problems.

Maintained by Johan Larsson. Last updated 1 days ago.

generalized-linear-models slope sparse-regression cpp openmp

17 stars 9.70 score 75 scripts 3 dependents

hazimehh

L0Learn:Fast Algorithms for Best Subset Selection

Highly optimized toolkit for approximately solving L0-regularized learning problems (a.k.a. best subset selection). The algorithms are based on coordinate descent and local combinatorial search. For more details, check the paper by Hazimeh and Mazumder (2020) <10.1287/opre.2019.1919>.

Maintained by Hussein Hazimeh. Last updated 2 years ago.

compressed-sensing feature-selection l0-regularization l0learn machine-learning regularization sparse-modeling sparse-regression openblas cpp

97 stars 7.14 score 95 scripts

gjjvdburg

sparsestep:SparseStep Regression

Implements the SparseStep model for solving regression problems with a sparsity constraint on the parameters. The SparseStep regression model was proposed in Van den Burg, Groenen, and Alfons (2017) <arXiv:1701.06967>. In the model, a regularization term is added to the regression problem which approximates the counting norm of the parameters. By iteratively improving the approximation a sparse solution to the regression problem can be obtained. In this package both the standard SparseStep algorithm is implemented as well as a path algorithm which uses golden section search to determine solutions with different values for the regularization parameter.

Maintained by Gertjan van den Burg. Last updated 4 years ago.

feature-selection lasso-variants regularized-linear-regression sparse-regression sparse-regularization

1 stars 2.70 score 7 scripts