Scaling

This section presents scaling applications, which transform the distribution of input variables to enhance data representation and analysis. Scaling methods adjust the range, shape, or spread of a distribution, making patterns more interpretable and ensuring consistency across variables. By mapping data to a new distribution, these transformations can highlight underlying structures, reduce biases, and improve model performance in various analytical workflows.

• Centered Log-Ratio Transformation
• Robust Tan Scaler Transformation