Ivan Palomares Carrascosa leaks some data:
In this article, you will learn what data leakage is, how it silently inflates model performance, and practical patterns for preventing it across common workflows.
Topics we will cover include:
- Identifying target leakage and removing target-derived features.
- Preventing train–test contamination by ordering preprocessing correctly.
- Avoiding temporal leakage in time series with proper feature design and splits.
Read on to learn more.