text: """
  =============================
  Recursive feature elimination
  =============================
  
  A recursive feature elimination example showing the relevance of pixels in
  a digit classification task.
  """
  print __doc__
  
  from sklearn.svm import SVC
  from sklearn.datasets import load_digits
  from sklearn.feature_selection import RFE
  
  # Load the digits dataset
  digits = load_digits()
  X = digits.images.reshape((len(digits.images), -1))
  y = digits.target
  
  # Create the RFE object and rank each pixel
  svc = SVC(kernel="linear", C=1)
  rfe = RFE(estimator=svc, n_features_to_select=1, step=1)
  rfe.fit(X, y)
  ranking = rfe.ranking_.reshape(digits.images[0].shape)
  
  # Plot pixel ranking
  import pylab as pl
  pl.matshow(ranking)
  pl.colorbar()
  pl.title("Ranking of pixels with RFE")
  pl.show()
  