•1 min read•from Data Science
Standardization vs Log transform ?
I have been trying to understand the use cases of both of these and I am really confused.
I know log transform fixes the features and makes their distribution normal and standardization on the other hand only fixes the scale of the feature by keeping the distribution the same.
Are these things which I use one after the other ? Or just simply use one depending on the case (which I also don't understand when) ?
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