Open Sandy4321 opened 2 years ago
Thanks for the note.
Not sure what you mean? Have you tried constructing a small example and then calling getPoly()?
Norm
On Sun, Jul 24, 2022 at 11:53:18AM -0700, Sandy4321 wrote:
great code (as what you doing )
"An important feature is that dummy variables are handled properly, so that for instance powers of a dummy variable do not exist as duplicates of the original."
just clarifying given categorical data
f1 f2 f3 a c u b g x a k y
after features interaction will it be for row N1 ?
f1 f2 f3 f1 f2 f3 f1 f2 f1f3 f2f3 f1f2f3 a c u => a c u ac au cu acu
to make sure there will not be ua, ca , ... uca , etc
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References
I ask you confirm if it works properly with categorical values What behavior to expect For long time I am looking for some theoretically correct design for categorical values features interaction
by the do you remove NEW muti-collinear (similar ) FEATURES since due to original features multiplication many very similar columns may be detected
great code (as what you doing )
"An important feature is that dummy variables are handled properly, so that for instance powers of a dummy variable do not exist as duplicates of the original."
just clarifying given categorical data
f1 f2 f3 a c u b g x a k y
after features interaction will it be for row N1 ?
f1 f2 f3 f1 f2 f3 f1 f2 f1f3 f2f3 f1f2f3 a c u => a c u ac au cu acu
to make sure there will not be ua, ca , ... uca , etc