Dev Tools · 2h ago
Two-Stage Workflow Detects Data Leakage in ML Models
A developer created a two-stage workflow to identify data leakage in machine learning models. Stage 1 checks linear relationships via correlation and single-feature R², flagging columns explaining over 10% of variance. Stage 2 uses tree-based models to detect non-linear leaks, helping prevent model failure in production.
Meridian48 take
This practical tool addresses a common ML pitfall, but its effectiveness depends on the quality of feature engineering and threshold choices.
data-leakagemachine-learning