elasticnet v1.02
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by Hui Zou
Elastic Net Regularization and Variable Selection
Efficient procedures for fitting an entire elastic net sequence. The elastic net methodology is described in the paper below. The package also implements the sparse PCA algorithm based on the elastic net/lasso.
Functions in elasticnet
| Name | Description | |
| predict.enet | Make predictions or extract coefficients from a fitted elastic net model | |
| print.spca | Print method for spca objects | |
| print.enet | Print method for enet objects | |
| enet | Fits Elastic Net regression models | |
| pitprops | Pitprops correlation data | |
| print.arrayspc | Print method for arrayspc objects | |
| plot.enet | Plot method for enet objects | |
| cv.enet | Computes K-fold cross-validated error curve for elastic net | |
| spca | Sparse Principal Components Analysis | |
| diabetes | Blood and other measurements in diabetics | |
| arrayspc | Sparse PCs of Microarrays | |
| elasticnet-internal | Internal elasticnet functions | |
| No Results! | ||
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Details
| Date | 2004-12-12 |
| License | GPL version 2 or newer |
| URL | http://www-stat.stanford.edu/~hzou/PAPERS/enet.pdf and http://www-stat.stanford.edu/~hzou/PAPERS/sparsepc.pdf |
| Packaged | Wed Dec 15 01:05:28 2004; hzou |
| depends | base , lars , R |
| Contributors | Hui Zou, Trevor Hastie |
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