fuseMLR: Fusing Machine Learning in R
Recent technological advances have enable the simultaneous collection
of multi-omics data i.e., different types or modalities of molecular data,
presenting challenges for integrative prediction modeling due to the heterogeneous,
high-dimensional nature and possible missing modalities of some individuals.
We introduce this package for late integrative prediction modeling, enabling
modality-specific variable selection and prediction modeling, followed by the
aggregation of the modality-specific predictions to train a final meta-model.
This package facilitates conducting late integration predictive modeling in a
systematic, structured, and reproducible way.
| Version: |
0.0.1 |
| Depends: |
R (≥ 3.6.0) |
| Imports: |
R6, stats, digest |
| Suggests: |
testthat (≥ 3.0.0), UpSetR (≥ 1.4.0), caret, ranger, glmnet, Boruta, knitr, rmarkdown, pROC, checkmate |
| Published: |
2024-12-17 |
| DOI: |
10.32614/CRAN.package.fuseMLR |
| Author: |
Cesaire J. K. Fouodo [aut, cre] |
| Maintainer: |
Cesaire J. K. Fouodo <cesaire.kuetefouodo at uni-luebeck.de> |
| BugReports: |
https://github.com/imbs-hl/fuseMLR/issues |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
fuseMLR results |
Documentation:
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