Study on the Lasso Method for Variable Selectionin Linear Regression Model with Mallows'' Cp
碩士 === 國立臺灣大學 === 數學研究所 === 95 === When the number of predictors in a linear regression model is large, regularization is a commonly used method to reduce the complexity of the fitted model. LASSO (Tibshirani, 1996) is being advocated as a useful regulation method for achieving sparsity or parsimony...
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/41127770529976845884 |