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Multivariate elastic net regression

Implements multivariate ("multi-target") elastic net regression through stacked generalisation (i.e., for multiple outcomes and many features).

Installation

Install the current release from CRAN:

install.packages("joinet")

or the latest development version from GitHub:

#install.packages("remotes")
remotes::install_github("rauschenberger/joinet")

Reference

Armin Rauschenberger and Enrico Glaab (2021). "Predicting correlated outcomes from molecular data”. Bioinformatics 37(21):3889–3895. doi: 10.1093/bioinformatics/btab576.

Disclaimer

The R package joinet implements multivariate elastic net regression through stacked generalisation (Rauschenberger & Glaab, 2021).

Copyright © 2019 Armin Rauschenberger, University of Luxembourg, Luxembourg Centre for Systems Biomedicine (LCSB), Biomedical Data Science (BDS)

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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Version

Install

install.packages('joinet')

Monthly Downloads

354

Version

1.0.0

License

GPL-3

Issues

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Stars

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Maintainer

Armin Rauschenberger

Last Published

September 27th, 2024

Functions in joinet (1.0.0)

predict.joinet

Make Predictions
cv.joinet

Model comparison
coef.joinet

Extract Coefficients
weights.joinet

Extract Weights
joinet-package

Multivariate Elastic Net Regression
joinet

Multivariate Elastic Net Regression