Model Drift
Degradation or change in model performance over time.
Definitions (4)
The phenomenon where an AI model’s behaviour, accuracy or fairness characteristics change over time due to evolving data, context or usage patterns, necessitating periodic reassessment, testing and remediation to maintain reliability.
The phenomenon where an AI model's performance degrades or its behavior changes over time due to shifts in input data distributions, environment, or use patterns, prompting revalidation, retraining, or other mitigation actions.
The degradation of a model's performance over time due to changes in the underlying data distribution.
The degradation of a model's performance over time, often due to changes in the underlying data or relationships, necessitating continuous monitoring and validation.
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