python - sklearn: how to get coefficients of polynomial features -

i know possible obtain polynomial features numbers using: polynomial_features.transform(x). according manual, degree of 2 features are: [1, a, b, a^2, ab, b^2]. how obtain description of features higher orders ? .get_params() not show list of features.

by way, there more appropriate function now: polynomialfeatures.get_feature_names.

from sklearn.preprocessing import polynomialfeatures import pandas pd import numpy np  data = pd.dataframe.from_dict({     'x': np.random.randint(low=1, high=10, size=5),     'y': np.random.randint(low=-1, high=1, size=5), })  p = polynomialfeatures(degree=2).fit(data) print p.get_feature_names(data.columns) 

this output follows:

['1', 'x', 'y', 'x^2', 'x y', 'y^2'] 

n.b. reason gotta fit polynomialfeatures object before able use get_feature_names().

if pandas-lover (as am), can form dataframe new features this:

features = dataframe(p.transform(data), columns=p.get_feature_names(data.columns)) print features 

result this:

     1    x    y   x^2  x y  y^2 0  1.0  8.0 -1.0  64.0 -8.0  1.0 1  1.0  9.0 -1.0  81.0 -9.0  1.0 2  1.0  1.0  0.0  1.0   0.0  0.0 3  1.0  6.0  0.0  36.0  0.0  0.0 4  1.0  5.0 -1.0  25.0 -5.0  1.0