👉 Blamability is a concept in machine learning that describes how well a model can be made to predict outcomes based on inputs. It is often used to evaluate models for their ability to generate accurate predictions, and it is closely related to the concept of "blaminess" or unpredictability. Blamability measures the extent to which a model's predictions are consistent with observed data in a specific context.
