PolynomialFeatures fit_transform is giving Value error
Question: 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>


Answer: 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.

