Model Drift
Model drift (also called concept drift) is the gradual decline in a machine learning model's predictive performance over time, occurring because the real-world relationship between inputs and the target outcome has changed since the model was trained.
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Glossary Terms(6)
AI Bias
AI bias refers to systematic errors in a machine learning model's outputs that unfairly favor or disadvantage particular groups or outcomes, typically arising…
AI Governance
AI governance is the set of policies, processes, roles, and controls that organizations and regulators put in place to ensure AI systems are developed and used…
Feature Store
A feature store is a centralized data system that stores, manages, and serves the engineered features used to train and run machine learning models, ensuring c…
Model Registry
A model registry is a centralized system for storing, versioning, and tracking machine learning models throughout their lifecycle, recording metadata such as t…
Model Drift
Model drift (also called concept drift) is the gradual decline in a machine learning model's predictive performance over time, occurring because the real-world…
Data Drift
Data drift is a change in the statistical distribution of a machine learning model's input data over time, which can degrade model performance even if the unde…