orthoMTL: Multi-Task Learning with Orthogonal Constraints
Fits regularised multi-task learning models where relationships
between tasks are controlled via orthogonality or disjoint-support constraints.
Supports regression, binary classification, and censored survival data.
In survival mode, time-to-event outcomes are converted into binary labels at
user-defined thresholds, enabling the discovery of features with time-varying
effects that standard proportional-hazards models cannot detect.
Implements the penalty described in Vervier et al. (2014)
<https://hal.science/hal-00985654>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
parallel, doParallel, foreach, ggplot2, rlang, stats |
| Suggests: |
knitr, glmnet, testthat (≥ 3.0.0), survival, rmarkdown |
| Published: |
2026-08-23 |
| DOI: |
10.32614/CRAN.package.orthoMTL |
| Author: |
Kevin Vervier [aut, cre],
Novartis Pharma AG [cph, fnd] |
| Maintainer: |
Kevin Vervier <kevin.vervier at novartis.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Citation: |
orthoMTL citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
orthoMTL results |
Documentation:
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