What is normalization in data transformation?
An example of an AI chatbot conversation about normalization in data transformation.
What is normalization in data transformation?
Normalization is the process of scaling data to fit within a specific range, often between 0 and 1.
Why is normalization important in data analysis?
Normalization helps to ensure that different features contribute equally to the analysis, improving model performance.
Can you explain the different methods of normalization?
Sure! Common methods include Min-Max scaling, Z-score normalization, and decimal scaling.
When should I use normalization versus standardization?
Use normalization when your data is bounded and you want to scale it to a specific range. Use standardization when your data follows a Gaussian distribution.
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