[scikit-learn] MinMaxScaler scales all (and only all) features in X?

Bill Ross bross_phobrain at sonic.net
Wed Jan 22 18:23:39 EST 2025


Hi, 

I have a mixture of table data and intermediate vectors from another
model, which don't seem to scale productively. The fact that
MinMaxScaler seems to do all features in X makes me wonder if/how people
train with such mixed data. 

The easy approaches seem to be either scale the db data and then combine
with the vectors, or just scale the db columns in place 'by hand'. 

Otherwise, I might consider adding a column-list option to the API. 

I suspect I'm just missing something important, since I wandered in
following this purely-tabular example, which seemed good before adding
ML-derived vectors: 

https://www.kaggle.com/code/carlmcbrideellis/tabular-classification-with-neural-networks-keras


Any advice or more-appropriate example to follow would be great. 

Thanks, 

Bill 

-- 
--

Phobrain.com
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mail.python.org/pipermail/scikit-learn/attachments/20250122/97257c9d/attachment.html>


More information about the scikit-learn mailing list