SVEMnet

Implements Self-Validated Ensemble Models (SVEM, Lemkus et al. (2021) doi:10.1016/j.chemolab.2021.104439) using Elastic Net regression via 'glmnet' (Friedman et al. doi:10.18637/jss.v033.i01). SVEM averages predictions from multiple models fitted to fractionally weighted bootstraps of the data, tuned with anti-correlated validation weights. Also implements the randomized permutation whole model test for SVEM (Karl (2024) doi:10.1016/j.chemolab.2024.105122). Code for the whole model test was taken from the supplementary material of Karl (2024). Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.

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