When should I use Z-score normalization?
An example of an AI chatbot conversation about when to apply Z-score normalization in data processing.
What is Z-score normalization?
Z-score normalization, or standardization, transforms data to have a mean of 0 and a standard deviation of 1.
When should I use Z-score normalization?
You should use Z-score normalization when your data follows a Gaussian distribution and you want to compare different datasets.
Are there any alternatives to Z-score normalization?
Yes, alternatives include Min-Max scaling and Robust scaling, which may be more suitable for non-Gaussian data.
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