Epistemic Uncertainty
Epistemic uncertainty refers to the uncertainty arising from a lack of knowledge or information about a system or process. In data science and artificial intelligence, epistemic uncertainty is often associated with model uncertainty, where the model used to make predictions or decisions is not a perfect representation of the underlying system. This can occur due to limited data, imperfect models, or incomplete understanding of the system. Epistemic uncertainty can be quantified using techniques such as Bayesian inference, which allows for the incorporation of prior knowledge and uncertainty into the model. Understanding and managing epistemic uncertainty is important in many applications of data science and artificial intelligence, such as decision-making in healthcare, finance, and autonomous systems.
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