Machine Learning Intermediate
nonstationarity
A feature whose values change across one or more dimensions, usually time.
Plain English Explanation
A feature whose values change across one or more dimensions, usually time. For example, consider the following examples of nonstationarity: - The number of swimsuits sold at a particular store varies with the season. - The quantity of a particular fruit harvested in a particular region is zero for much of the year but large for a brief period. - Due to climate change, annual mean temperatures are shifting. Contrast with stationarity.
How is it used?
Practitioners refer to nonstationarity when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.