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: | 0.0.2 |
| 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: | 2025-10-13 |
| 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 |
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