title: PolynomialFeatures Sklearn (many parameters)
body: <p>Here is my code.</p>
  
  <pre><code> import numpy as np
   from sklearn.preprocessing import PolynomialFeatures
   from sklearn.linear_model import LinearRegression
   X=np.array([[1, 2, 4]]).T
   print(X)
   y=np.array([1, 4, 16])
   print(y)
   X_poly = PolynomialFeatures(degree=2).fit_transform(X)
   print(X_poly)
   # fit_intercept = False since PolynomialFeatures will create a 0-order   
   polynomial as well.
   model = LinearRegression(fit_intercept = False)
   model.fit(X_poly,y)
  
  print('Coefficients: \n', model.coef_)
  print('Others: \n', model.intercept_)
  </code></pre>
  
  <p>Please, how can change this code to use many parameters.
  Example of models:</p>
  
  <pre><code>y=a*x*x+b * z+ c* t (we have y, x, z and t)
  </code></pre>
  
  <p>Thanks a lot for help.
  Kind regards. </p>