gp3ml: Governance-First Predictive Modelling for 'Gazepoint' Research
Provides governance-first infrastructure for leakage-resistant
predictive modelling and validation using 'Gazepoint'-derived research
data. Supports explicit task and role declarations, feature-provenance
manifests, group-aware holdout splitting and repeated resampling,
fold-local preprocessing, governed model engines, discrimination and
calibration metrics, bootstrap uncertainty, external-validation
reports, model cards, and reproducibility reports. Intended only for
explicitly observed, non-sensitive outcomes and declared scientific
purposes. Use is prohibited for person identification, biometric
authentication, health or protected-attribute inference, and direct or
indirect inference of emotion, stress, personality, deception,
cognition, comprehension, intent, or other mental states.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Suggests: |
jsonlite, keras3, knitr, nnet, pkgdown, ranger, rmarkdown, testthat (≥ 3.0.0), xgboost |
| Published: |
2026-07-30 |
| DOI: |
10.32614/CRAN.package.gp3ml |
| Author: |
Stefanos Balaskas 
[aut, cre] |
| Maintainer: |
Stefanos Balaskas <s.balaskas at ac.upatras.gr> |
| BugReports: |
https://github.com/stefanosbalaskas/gp3ml/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://stefanosbalaskas.github.io/gp3ml/,
https://github.com/stefanosbalaskas/gp3ml |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README, NEWS |
| CRAN checks: |
gp3ml results |
Documentation:
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