Which method is commonly used to handle missing data in a dataset?
- Data normalization
- Mean imputation
- One-hot encoding
- Outlier detection
Mean imputation is a common method used to handle missing data. It involves replacing missing values with the mean of the observed values in that column, providing a simple way to fill in gaps without introducing bias.
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