AI engineering glossary · ML fundamentals
What is temporal leakage?
Temporal leakage (also called Look-ahead bias): Leakage that occurs when data from the future is used to predict the past, for example by randomly shuffling time-ordered data before splitting or by computing features with later information. It makes forecasts look far more accurate than they can ever be live.
Temporal leakage: an example
Using the full-year average sales as a feature for predicting sales in March lets the model know about December.
Related terms
More ML fundamentals terms
- Test set
- Time-series split
- Train-test contamination
- Training
- Training error
- Training example
- Training set
- Transfer learning
Where you learn it
Temporal leakage is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.