How do you deal with missing or incomplete data when estimating prior or posterior probabilities?
Missing or incomplete data is a common challenge when you want to estimate prior or posterior probabilities for decision analysis. Prior probabilities represent your initial beliefs or assumptions about a situation, while posterior probabilities reflect how you update those beliefs after observing new evidence. In this article, you will learn how to deal with missing or incomplete data when estimating prior or posterior probabilities, and what are some of the advantages and disadvantages of different methods.
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Gabriela DemarchiInsights, Analytics and Strategy Manager | Turning Your Data into Dynamic Business Strategies & Growth | Expertise in…
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G Harshavardhan ReddyWorking @DRDO
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HIMANSHU NEGI?~25,000 followers | Gen AI | MLOps | LLM | Author | Mentor | Double Masters in AI | Follow to get latest tech updates