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I am using MinMaxScaler on a large dataset (2201887, 3) to normalize features. Inversed values does not match originals. I tested with the target column, first (a), I applied the scaler on 10 values, then did the inverse transformation and I was able to get original values. Then (b), I inverted 10 normalized values after applying MinMaxScaler on the whole column and results were completely different : enter image description here

Result of (a) :

enter image description here

Result of (b) :

enter image description here

How can I have the same normalized and inversed values when used with the whole dataset?

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I wasn't able to reproduce the issue as inverse_transform(b) threw an error because it was trained on a (,3) array but the input is only (,1). Not sure if I typoed or how your code runs.

You could try instantiating a new MinMaxScaler, as I'm not sure if anything weird happens if you refit it.

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  • $\begingroup$ Yes I think that was the problem, I used inverse_transform() on the whole transformed data that has the shape (,3) and it generated the same original values. Thank you for your help. $\endgroup$
    – Bochra BEN JABALLAH
    Commented Jul 7, 2021 at 14:59

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