I am getting a ValueError while trying to run the Polynomial Regression example:
from sklearn.preprocessing import PolynomialFeatures
import numpy as np
poly = PolynomialFeatures(degree=2)
poly.fit_transform(X) ==> ERROR
The error is:
File "/root/.local/lib/python2.7/site-packages/sklearn/base.py", line 426, in fit_transform
return self.fit(X, **fit_params).transform(X)
File "/root/.local/lib/python2.7/site-packages/sklearn/preprocessing/data.py", line 473, in fit
self.include_bias)
File "/root/.local/lib/python2.7/site-packages/sklearn/preprocessing/data.py", line 463, in _power_matrix
powers = np.vstack(np.bincount(c, minlength=n_features) for c in combn)
File "/usr/lib/python2.7/dist-packages/numpy/core/shape_base.py", line 226, in vstack
return _nx.concatenate(map(atleast_2d,tup),0)
File "/root/.local/lib/python2.7/site-packages/sklearn/preprocessing/data.py", line 463, in <genexpr>
powers = np.vstack(np.bincount(c, minlength=n_features) for c in combn)
ValueError: The first argument cannot be empty.
My scikit-learn version is 0.15.2
This is example is taken from: http://scikit-learn.org/stable/modules/linear_model.html#polynomial-regression-extending-linear-models-with-basis-functions
You should try to set include_bias to False when creating object of PolynomialFeatures class like this
poly = PolynomialFeatures(degree=2, include_bias=False)
Note that the final matrix in the example does not have the first column now.
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