Efficient algorithms for fitting the regularization path of linear or logistic regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.
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Summary
Efficient algorithms for fitting the regularization path of linear or logistic regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.
Information Last Updated
Mar 25, 2025 at 16:21
License
GPL-3
Total Downloads
21
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