Machine Learning Intermediate
stationarity
A feature whose values don't change across one or more dimensions, usually time.
Plain English Explanation
A feature whose values don't change across one or more dimensions, usually time. For example, a feature whose values look about the same in 2021 and 2023 exhibits stationarity. In the real world, very few features exhibit stationarity. Even features synonymous with stability (like sea level) change over time. Contrast with nonstationarity.
How is it used?
Practitioners refer to stationarity when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.