Abstract
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such models, but usually involves a computationally heavy combinatorial search. Lasso (Tibshirani, 1996) is now being used as a computationally feasible alternative to model selection.
Keywords
Lasso (programming language)Model selectionSelection (genetic algorithm)Feature selectionConsistency (knowledge bases)Elastic net regularizationCovarianceComputer scienceVerifiable secret sharingMathematicsRepresentation (politics)Machine learningArtificial intelligenceAlgorithmStatistics
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Publication Info
- Year
- 2006
- Type
- article
- Volume
- 7
- Issue
- 90
- Pages
- 2541-2563
- Citations
- 1986
- Access
- Closed
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1986
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Cite This
Peng Zhao,
Bin Yu
(2006).
On Model Selection Consistency of Lasso.
, 7
(90)
, 2541-2563.