Tag: feature selection

A long-form feature-screening workflow that uses correlation for quick linear checks, then adds redundancy clustering, mutual information, chi-squared tests, L1 models, tree importances, permutation importance, and domain review.

Outcome: Defined a practical feature review loop that prevents teams from dropping useful nonlinear signals or keeping redundant features just because a correlation heatmap looked convincing.