In which scenario would Min-Max normalization be a less ideal choice for data scaling?

  • When outliers are present
  • When the data has a normal distribution
  • When the data will be used for regression analysis
  • When interpretability of features is crucial
Min-Max normalization can be sensitive to outliers. If outliers are present in the data, this scaling method can compress the majority of data points into a narrow range, making it less suitable for preserving the information in the presence of outliers. In scenarios where outliers are a concern, alternative scaling methods like Robust Scaling may be preferred.
Add your answer
Loading...

Leave a comment

Your email address will not be published. Required fields are marked *