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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