Implements transfer learning methods for low-rank matrix estimation. These methods leverage similarity in the latent row and column spaces between the source and target populations to improve estimation in the target population. The methods include the LatEnt spAce-based tRaNsfer lEaRning (LEARNER) method and the direct projection LEARNER (D-LEARNER) method described by McGrath et al. (2024) <doi:10.48550/arXiv.2412.20605>.
Version: | 0.1.0 |
Depends: | R (≥ 2.10) |
Imports: | doParallel, foreach, ScreeNOT |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2025-01-08 |
DOI: | 10.32614/CRAN.package.learner |
Author: | Sean McGrath [aut, cre], Cenhao Zhu [aut], Rui Duan [aut] |
Maintainer: | Sean McGrath <sean.mcgrath514 at gmail.com> |
BugReports: | https://github.com/stmcg/learner/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/stmcg/learner |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | learner results |
Reference manual: | learner.pdf |
Package source: | learner_0.1.0.tar.gz |
Windows binaries: | r-devel: learner_0.1.0.zip, r-release: learner_0.1.0.zip, r-oldrel: learner_0.1.0.zip |
macOS binaries: | r-release (arm64): learner_0.1.0.tgz, r-oldrel (arm64): learner_0.1.0.tgz, r-release (x86_64): learner_0.1.0.tgz, r-oldrel (x86_64): learner_0.1.0.tgz |
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