A Model Selection Criterion for LASSO Estimate with Scaling
| Autor: | Katsuyuki Hagiwara |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
021103 operations research
Model selection 0211 other engineering and technologies Estimator 02 engineering and technology 01 natural sciences Statistics::Computation 010104 statistics & probability Lasso (statistics) Simple (abstract algebra) Statistics::Methodology Applied mathematics 0101 mathematics Analytic solution Scaling Selection operator Mathematics |
| Zdroj: | Neural Information Processing ISBN: 9783030367107 ICONIP (2) |
| DOI: | 10.1007/978-3-030-36711-4_22 |
| Popis: | There have been several studies to relax a bias problem in LASSO (Least Absolute Shrinkage and Selection Operator). In this article, we considered to solve a bias problem of LASSO estimator by scaling and derived a model selection criterion under the scaling method. The proposed scaling value is valid to compensate the excessive shrinkage of LASSO estimator and is easy to compute by using LASSO estimator. Moreover, we derived SURE (Stein’s Unbiased Risk Estimate) as a model selection criterion. This analytic solution is also a benefit of the proposed scaling value. Furthermore, we verified the risk estimate and confirmed its effectiveness through a simple numerical example. |
| Databáze: | OpenAIRE |
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