In predictive analytics and machine learning, the concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions become less accurate as time passes.
The term concept refers to the quantity to be predicted. More generally, it can also refer to other phenomena of interest besides the target concept, such as an input, but, in the context of concept drift, the term commonly refers to the target variable.
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Famous quotes containing the words concept and/or drift:
“Terror is as much a part of the concept of truth as runniness is of the concept of jam. We wouldn’t like jam if it didn’t, by its very nature, ooze. We wouldn’t like truth if it wasn’t sticky, if, from time to time, it didn’t ooze blood.”
—Jean Baudrillard (b. 1929)
“But now they drift on the still water,
Mysterious, beautiful;”
—William Butler Yeats (1865–1939)