如何在 MinMaxScaler 中反向归一化

Question

i have a data that range between 0 - 2,9.

I need it to be normalized with MinMaxScaler with 0 - 1 range.

I need to transform 2.9 into 0 and 0 into 1. My solution is to subtract all numbers with 2.9 and make it absolute. But is there any other way more efficient than that? I'm using sklearn for normalization

Answer 1

All you have to do is to multiply your data by -1 prior to normalization. With that your max value (2.9) becomes the new min value (-2.9) that gets normalized to 0 and your min (0) becomea the new max that gets normalized to 1.