Prevent Data Leakage in ML Pipelines

Data leakage occurs when ML models accidentally access information during training that won't be available during inference, causing artificially high training accuracy but poor real-world performance. Common causes include train/test contamination, preprocessing with combined dataset statistics, and using target-derived Show more