Package: NumericEnsembles 1.2.1

NumericEnsembles: Multi-Model Stacking Optimization and Continuous Regression Ensembles

Automated parallelized regression ensemble pipeline executing concurrent evaluations across 17 base machine learning architectures, 6 specialized stacking meta-learners, and 136 pairwise hybrid combinations. The package implements dynamic performance-weighted stacking blends alongside internal data dictionary profiling metrics. It provides iterative multicollinearity pruning via Variance Inflation Factors (VIF) and automated executive Quarto report generation.

Authors:Russ Conte [aut, cre, cph]