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Perform variable selection in settings with possibly missing data based on extrinsic (algorithm-specific) and intrinsic (population-level) variable importance. Uses a Super Learner ensemble to estimate the underlying prediction functions that give rise to estimates of variable importance. For more information about the methods, please see Williamson and Huang (2023+) <arXiv:2202.12989>.
Package details |
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Author | Brian D. Williamson [aut, cre] (<https://orcid.org/0000-0002-7024-548X>) |
Maintainer | Brian D. Williamson <brian.d.williamson@kp.org> |
License | MIT + file LICENSE |
Version | 0.0.4 |
URL | https://github.com/bdwilliamson/flevr |
Package repository | View on CRAN |
Installation |
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