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MLmorph: Integrating Morphological Modeling and Machine Learning for
Decision Support
Integrating morphological modeling with machine learning to support
structured decision-making (e.g., in management and consulting). The package
enumerates a morphospace of feasible configurations and uses random forests
to estimate class probabilities over that space, bridging deductive model
exploration with empirical validation. It includes utilities for factorizing
inputs, model training, morphospace construction, and an interactive 'shiny'
app for scenario exploration.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.3.0) |
| Imports: |
caret (≥ 6.0.94), jsonlite (≥ 1.8.8), magrittr, openxlsx (≥
4.2.5.2), randomForest (≥ 4.7.1.1), shiny (≥ 1.10.0), stats (≥ 4.3.0), tidyr (≥ 1.3.1), utils (≥ 4.3.0) |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2025-09-02 |
| DOI: |
10.32614/CRAN.package.MLmorph |
| Author: |
Oskar Kosch  [aut,
cre, cph] |
| Maintainer: |
Oskar Kosch <contact at oskarkosch.com> |
| BugReports: |
https://github.com/theogrost/MLmorph/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/theogrost/MLmorph |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README, NEWS |
| CRAN checks: |
MLmorph results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.