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How do you handle missing or corrupted data in a dataset?
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Answer / Sameer Alam
Handling missing or corrupted data can be achieved through techniques like Imputation, where missing values are replaced with statistical measures (Mean/Median Imputation), and Multiple Imputation to account for the uncertainty. For corrupted data, methods such as Data Cleaning, Outlier Detection, and Regression with Error Detection can be used.
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