What is min-max scaling?
An example of an AI chatbot conversation about min-max scaling in data normalization.
Can you explain what min-max scaling is?
Min-max scaling is a normalization technique that transforms features to a fixed range, usually [0, 1].
Why is min-max scaling important in machine learning?
It's important because it helps to ensure that all features contribute equally to the distance calculations in algorithms.
How do you apply min-max scaling to a dataset?
You apply it by subtracting the minimum value of the feature and then dividing by the range (max - min).
Are there any drawbacks to using min-max scaling?
Yes, it can be sensitive to outliers, which can skew the scaling.
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