Distribution shift – Definition & Meaning

Definition of distribution shift

: a difference between the statistical distribution of the data used to train or evaluate a model and the data the model encounters after deployment
- The diagnostic model lost accuracy after a distribution shift caused by the hospital replacing its imaging equipment.
- Seasonal buying behavior created a distribution shift that was not represented in the original training data.

Two meanings, one word

In everyday English

A shift is a change in position, direction, or condition.

In AI

A difference between the statistical distribution of the data used to train or evaluate a model and the data the model encounters after deployment.

Origin & history

first known use2008

Machine-learning researchers studied changes between training and test distributions before the term was standardized. The 2008 MIT Press volume 'Dataset Shift in Machine Learning' consolidated the area and distinguished general dataset shift from cases such as covariate shift.

Test yourself

Which of these is the meaning of distribution shift?

Related terms

training data the collection of examples (text, images, code, audio, and so on) that a model learns from test-time training a method that updates a model at deployment time using a learning signal derived from the… fine-tuning further training of an existing model on a smaller, focused dataset so it gets better at a… inference the act of running a trained model to produce an output, such as answering a prompt or… neural network a computing system made of many simple connected units ("neurons") arranged in layers, which… foundation model a large model trained on broad data that can be adapted to many different tasks, serving as…

Cite this entry

"Distribution shift." AI Dictionary, Dadgogo, https://dadgogo.com/dictionary/distribution-shift/. Accessed 6 Oct. 2026.