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joinet: Penalised Multivariate Regression ('Multi-Target Learning')
Implements penalised multivariate regression (i.e., for multiple outcomes and many features) by stacked generalisation (<doi:10.1093/bioinformatics/btab576>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. For optional comparisons, install 'remMap' from GitHub (<https://github.com/cran/remMap>).
Getting started
Browse package contents
Package details |
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| Author | Armin Rauschenberger [aut, cre] (<https://orcid.org/0000-0001-6498-4801>) |
| Maintainer | Armin Rauschenberger <armin.rauschenberger@uni.lu> |
| License | GPL-3 |
| Version | 1.0.0 |
| URL | https://github.com/rauschenberger/joinet https://rauschenberger.github.io/joinet/ |
| Package repository | View on CRAN |
| Installation |
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