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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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