Sample Selection Bias — Distribution distortion that occurs when observed data does not represent the full population

Sample Selection Bias is a distribution distortion problem that arises when the data we observe does not fairly represent the full population, but only the subset selected through a particular condition or process. Because of this, a model may fit the training data well while performing much worse in the real world.

03/27/2026