I know it is possible to obtain the polynomial features as numbers by using: polynomial_features.transform(X). According to the manual, for a degree of two the features are: [1, a, b, a^2, ab, b^2]. But how do I obtain a description of the features for higher orders ? .get_params() does not show any list of features.
By the way, there is more appropriate function now: PolynomialFeatures.get_feature_names.
from sklearn.preprocessing import PolynomialFeatures
import pandas as pd
import numpy as 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 will output as follows:
['1', 'x', 'y', 'x^2', 'x y', 'y^2']
N.B. For some reason you gotta fit your PolynomialFeatures object before you will be able to use get_feature_names().
If you are Pandas-lover (as I am), you can easily form DataFrame with all new features like this:
features = DataFrame(p.transform(data), columns=p.get_feature_names(data.columns))
print features
Result will look like 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