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How to Detect Outliers in Data Preprocessing? A Guide for Data Scientists ️

  • As data scientists, it is important to detect and handle outliers in data preprocessing.
  • Two powerful methods to detect outliers are Z-score and Interquartile Range (IQR).
  • Z-score measures the number of standard deviations a data point is away from the mean.
  • A Z-score greater than 3 or less than -3 indicates an outlier.

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