You are tasked with preparing a dataset for use in a machine learning algorithm that does not assume any specific distribution of the data. Which scaling method might be most appropriate?
- Min-Max scaling because it scales all values between 0 and 1
- Robust scaling because it is not affected by outliers
- The choice of scaling method does not depend on the distribution of the data
- Z-score standardization because it creates a normal distribution
The choice of scaling method does not depend on the distribution of the data but rather on the properties of the data and the requirements of the specific algorithm being used. All scaling methods could potentially be appropriate depending on other factors such as the presence of outliers, the need to maintain the range of the data, etc.
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