solegalli1 at gmail.com
Mon Nov 25 05:12:06 EST 2019
Hi Michael, Nicolas,
Thank you both, that is very helpful!
On Sun, 24 Nov 2019 at 03:37, Michael Eickenberg <
michael.eickenberg at gmail.com> wrote:
> 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
> scikit-learn mailing list
> scikit-learn at python.org
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