Hi Michael, Nicolas, Thank you both, that is very helpful! Best wishes Sole On Sun, 24 Nov 2019 at 03:37, Michael Eickenberg < michael.eickenberg@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@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, include_bias=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: a; b; c; (a+b)^2 (a+b)^3 (a+c)^2 (a+c)^3 (c+b)^2 (c+b)^3 (a+b+c)^2 (a+b+c)^3
And the transform() generates the expansion, without the constant that multiplies the interactions and avoiding duplicated terms after the expansion?
Thanks for the help.
Kind regards
Sole
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