The A to Z of dealing with Outliers | Data Preprocessing | Data Science

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  • เผยแพร่เมื่อ 5 พ.ย. 2024

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  • @janaosama6010
    @janaosama6010 8 หลายเดือนก่อน +1

    we find out that the outliers in our data is true/genuine outliers so we should keep them, then if we want to calculate the mean and use it in handling missing values for example so it will be safe to use it with the presence of the outliers because they’re actual outliers and their effect on the mean is meaningful?
    Same question as using Linear regression model because it’s sensitive to outliers can we use it too?
    Thanks in advance

    • @prosmartanalytics
      @prosmartanalytics  8 หลายเดือนก่อน

      In the presence of genuine outlier values we should use median instead of mean for all descriptive purposes. But if we have outliers present, we should definitely avoid linear regression; instead, we should use models which are not sensitive towards outliers.

  • @rachitmakhija9703
    @rachitmakhija9703 ปีที่แล้ว

    when will the hands on piece get uploaded ??