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ReSurv: Machine Learning Models for Predicting Claim Counts
Prediction of claim counts using the feature based development factors introduced in the manuscript Hiabu M., Hofman E. and Pittarello G. (2023) <doi:10.48550/arXiv.2312.14549>. Implementation of Neural Networks, Extreme Gradient Boosting, and Cox model with splines to optimise the partial log-likelihood of proportional hazard models.
Getting started
Browse package contents
Package details |
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| Author | Emil Hofman [aut, cre, cph], Gabriele Pittarello [aut, cph] (<https://orcid.org/0000-0003-3360-5826>), Munir Hiabu [aut, cph] (<https://orcid.org/0000-0001-5846-667X>) |
| Maintainer | Emil Hofman <emil_hofman@hotmail.dk> |
| License | GPL (>= 2) |
| Version | 1.0.0 |
| URL | https://github.com/edhofman/ReSurv |
| Package repository | View on CRAN |
| Installation |
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