I have a feature with data creation dates. I have normalized them all to the same format and split them to 'day', 'month' and 'year' columns. But now I have a question. Should I apply normalization or standardization to these columns, or on dates this does not have sense?
Topic data-wrangling data-cleaning
Category Data Science
You might want to apply one-hot encoding instead. These are not really continuous features. If you consider each day of the week or month of the year a category, then you can instead treat them as categorical variables.
The year is trickier as it does not repeat itself. I would suggest to maybe instead of using the year to use a date difference: which can now be treaded as a continuous variable. You can do any regular scaling (standard scaling, max abs scaling ...)
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