R2 Scoring for SFS

[Anuj-Saboo]

Hi,

I have used SFS from mlxtend with r2 scorer. The thing about R2 is that in regression models, with addition of new features R2 will always increase. Hence, is it ever useful to use R2 as a scorer or should a custom function with adjusted r2 be always used?

While I have seen R2 used in practice, I have seen the plot where with more features I see R2 dropping. For example in this notebook https://www.kaggle.com/code/jorijnsmit/linear-regression-by-sequential-feature-selection the validation section has the SFS plot where R2 is dropping on adding new features.

Can someone pls help me understand how this is possible?