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matrans  

Model Averaging-Assisted Optimal Transfer Learning
View on CRAN: Click here


Download and install matrans package within the R console
Install from CRAN:
install.packages("matrans")

Install from Github:
library("remotes")
install_github("cran/matrans")

Install by package version:
library("remotes")
install_version("matrans", "0.1.0")



Attach the package and use:
library("matrans")
Maintained by
Xiaonan Hu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-12
Latest Update: 2024-01-12
Description:
Transfer learning, as a prevailing technique in computer sciences, aims to improve the performance of a target model by leveraging auxiliary information from heterogeneous source data. We provide novel tools for multi-source transfer learning under statistical models based on model averaging strategies, including linear regression models, partially linear models. Unlike existing transfer learning approaches, this method integrates the auxiliary information through data-driven weight assignments to avoid negative transfer. This is the first package for transfer learning based on the optimal model averaging frameworks, providing efficient implementations for practitioners in multi-source data modeling. The details are described in Hu and Zhang (2023) .
How to cite:
Xiaonan Hu (2024). matrans: Model Averaging-Assisted Optimal Transfer Learning. R package version 0.1.0, https://cran.r-project.org/web/packages/matrans. Accessed 21 Nov. 2024.
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Complete documentation for matrans
Functions, R codes and Examples using the matrans R package
Some associated functions: pred.transsmap . simdata.gen . trans.smap . 
Some associated R codes: pred.transsmap.R . simdata.gen.R . trans.smap.R .  Full matrans package functions and examples
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