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HMTL  

Heterogeneous Multi-Task Feature Learning
View on CRAN: Click here


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

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

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



Attach the package and use:
library("HMTL")
Maintained by
Yuan Zhong
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-05-04
Latest Update: 2023-05-04
Description:
The heterogeneous multi-task feature learning is a data integration method to conduct joint feature selection across multiple related data sets with different distributions. The algorithm can combine different types of learning tasks, including linear regression, Huber regression, adaptive Huber, and logistic regression. The modified version of Bayesian Information Criterion (BIC) is produced to measure the model performance. Package is based on Yuan Zhong, Wei Xu, and Xin Gao (2022) .
How to cite:
Yuan Zhong (2023). HMTL: Heterogeneous Multi-Task Feature Learning. R package version 0.1.0, https://cran.r-project.org/web/packages/HMTL. Accessed 22 Dec. 2024.
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Complete documentation for HMTL
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