Multi-omics (synthetic) — load, sanity checks, DR, and correlations

emonstrates how to train, evaluate, and apply a **Random Forest classifier** on microbiome relative abundance data. It includes preprocessing, cross-validation, model tuning, and visualization of prediction probabilities — including **faceted heatmaps grouped by diet**.