michael.eickenberg at gmail.com
Sat Nov 23 21:35:39 EST 2019
I think it might generate a basis that is capable of generating what you
describe above, but feature expansion concretely reads as
1, a, b, c, a ** 2, ab, ac, b ** 2, bc, c ** 2, a ** 3, a ** 2 * b, a ** 2
* c, a* b ** 2, abc, a*c**2, b**3, b**2 * c, b*c**2, c**3
Hope this helps
On Fri, Nov 22, 2019 at 8:50 AM Sole Galli <solegalli1 at gmail.com> wrote:
> Hello team,
> Can I double check with you that I understand correctly what the
> PolynomialFeatures() is doing under the hood?
> If I set it like this:
> poly = PolynomialFeatures(degree=3, interaction_only=False,
> and I fit it on a dataset with 3 variables, a,b and c.
> Am I correct to say that the fit() method creates all possible
> combinations like this:
> And the transform() generates the expansion, without the constant that
> multiplies the interactions and avoiding duplicated terms after the
> Thanks for the help.
> Kind regards
> scikit-learn mailing list
> scikit-learn at python.org
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