We provide an efficient implementation for two-step multi-source transfer learning algorithms in high-dimensional generalized linear models (GLMs). The elastic-net penalized GLM with three popular families, including linear, logistic and Poisson regression models, can be fitted. To avoid negative transfer, a transferable source detection algorithm is proposed. We also provides visualization for the transferable source detection results. The details of methods can be found in "Tian, Y., & Feng, Y. (2023). Transfer learning under high-dimensional generalized linear models. Journal of the American Statistical Association, 118(544), 2684-2697.".
Package details |
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Author | Ye Tian [aut, cre], Yang Feng [aut] |
Maintainer | Ye Tian <ye.t@columbia.edu> |
License | GPL-2 |
Version | 2.1.0 |
Package repository | View on CRAN |
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