Survival Analysis for Data Drift and ML Reliability

Short summary

Survival analysis, a statistical method for modeling time-to-failure, can be applied to predict ML model degradation from data drift. This frames model reliability as a statistical problem rather than traditional metrics, offering a novel framework for production ML monitoring and failure prediction.

• •Applies survival analysis methods to model degradation and data drift prediction
• •Frames ML reliability as a time-to-failure problem
• •Relevant for teams managing production model monitoring and system reliability

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