I have a dataset with 3 independent variables [city, industry, amount] and wish to normalize the amount. But I wish to do it with respect to industry and city. Simply grouping by the city and industry gives me a lot of very sparse groups on which normalizing (min-max, etc.) wouldn't be very meaningful. Is there any better way to normalize it?
Topic preprocessing feature-scaling machine-learning
Category Data Science
Normalization is typically done to each feature separately.
Normalization means different operations for numerical vs. categorical data. It appears amount is numerical. As you mention, amount could be min-max rescaled. City and industry appear to be categorical. Categorical normalization typically means grouping related entities together. That is often a manual process.
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