How to Transform Data to Better Fit The Normal Distribution (Box Cox transformation)

I would like to know if there is an easy way to Transform Data to Better Fit The Normal Distribution.

A Box Cox transformation node or something like that.

I set a of data multiple columns and with different patterns and I need to transform everything into a normal shape.

Best regards

Hi,

You could try Z-scale normalization (Gaussian) with the Normalizer node:

Linear transformation such that the values in each column are Gaussian-(0,1)-distributed, i.e. mean is 0.0 and standard deviation is 1.0.

Cheers/Evert

Hi @AR7 and welcome back to the forum

We have a feature request open to add Box-Cox functionality and power transformation in general. I will add a +1 on that request from you (AP-13756).

In the meantime you could, for example, use an R Snippet with a few lines of code to quickly determine and apply Box-Cox.

Hi I found this on Stack Overflow

Cheers

r boX-cOX.knwf (111.3 KB)

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