Package: HMTL
Type: Package
Title: Heterogeneous Multi-Task Feature Learning
Version: 0.1.0
Authors@R: c(person("Yuan", "Zhong",role=c("aut","cre"),email = "aqua.zhong@gmail.com"), person("Wei","Xu",role = "aut"), person("Xin","Gao",role = "aut"))
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)
        <https://www.fields.utoronto.ca/talk-media/1/53/65/slides.pdf>.
Depends: R (>= 3.5.0), stats, graphics, Matrix, pROC
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2026-07-17 06:01:23 UTC; root
Author: Yuan Zhong [aut, cre], Wei Xu [aut], Xin Gao [aut]
Maintainer: Yuan Zhong <aqua.zhong@gmail.com>
Repository: https://hermitz9.r-universe.dev
Date/Publication: 2023-05-04 18:20:02 UTC
RemoteUrl: https://github.com/cran/HMTL
RemoteRef: HEAD
RemoteSha: f00b438e842be937fe5036a4fce9cddf1006c4fd