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LassoBacktracking: Modelling Interactions in High-Dimensional Data with Backtracking
Implementation of the algorithm introduced in Shah, R. D. (2016) <https://www.jmlr.org/papers/volume17/13-515/13-515.pdf>. Data with thousands of predictors can be handled. The algorithm performs sequential Lasso fits on design matrices containing increasing sets of candidate interactions. Previous fits are used to greatly speed up subsequent fits, so the algorithm is very efficient.
Getting started
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Package details |
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| Author | Rajen Shah [aut, cre] |
| Maintainer | Rajen Shah <r.shah@statslab.cam.ac.uk> |
| License | GPL (>= 2) |
| Version | 1.1 |
| URL | https://www.jmlr.org/papers/volume17/13-515/13-515.pdf |
| Package repository | View on CRAN |
| Installation |
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