old_contents: """
  Machine Learning module in python
  =================================
  
  scikits.learn is a Python module integrating classique machine
  learning algorithms in the tightly-nit world of scientific Python
  packages (numpy, scipy, matplotlib).
  
  It aims to provide simple and efficient solutions to learning problems
  that are accessible to everybody and reusable in various contexts:
  machine-learning as a versatile tool for science and engineering.
  
  See http://scikit-learn.sourceforge.net for complete documentation.
  """
  
  from .base import clone
  
  
  try:
      from numpy.testing import nosetester
  
      class NoseTester(nosetester.NoseTester):
          """ Subclass numpy's NoseTester to add doctests by default
          """
  
          def test(self, label='fast', verbose=1, extra_argv=['--exe'],
                          doctests=True, coverage=False):
              return super(NoseTester, self).test(label=label, verbose=verbose,
                                      extra_argv=extra_argv,
                                      doctests=doctests, coverage=coverage)
  
      test = NoseTester().test
      del nosetester
  except:
      pass
  
  
  __all__ = ['cross_val', 'ball_tree', 'cluster', 'covariance', 'datasets',
             'decomposition', 'feature_extraction', 'feature_selection',
             'gaussian_process', 'grid_search', 'hmm', 'lda', 'linear_model',
             'metrics', 'mixture', 'naive_bayes', 'neighbors', 'pipeline',
             'preprocessing', 'qda', 'svm', 'test', 'clone', 'pls']
  
  __version__ = '0.9-git'
  
new_contents: """
  Machine Learning module in python
  =================================
  
  scikits.learn is a Python module integrating classical machine
  learning algorithms in the tightly-knit world of scientific Python
  packages (numpy, scipy, matplotlib).
  
  It aims to provide simple and efficient solutions to learning problems
  that are accessible to everybody and reusable in various contexts:
  machine-learning as a versatile tool for science and engineering.
  
  See http://scikit-learn.sourceforge.net for complete documentation.
  """
  
  from .base import clone
  
  
  try:
      from numpy.testing import nosetester
  
      class NoseTester(nosetester.NoseTester):
          """ Subclass numpy's NoseTester to add doctests by default
          """
  
          def test(self, label='fast', verbose=1, extra_argv=['--exe'],
                          doctests=True, coverage=False):
              return super(NoseTester, self).test(label=label, verbose=verbose,
                                      extra_argv=extra_argv,
                                      doctests=doctests, coverage=coverage)
  
      test = NoseTester().test
      del nosetester
  except:
      pass
  
  
  __all__ = ['cross_val', 'ball_tree', 'cluster', 'covariance', 'datasets',
             'decomposition', 'feature_extraction', 'feature_selection',
             'gaussian_process', 'grid_search', 'hmm', 'lda', 'linear_model',
             'metrics', 'mixture', 'naive_bayes', 'neighbors', 'pipeline',
             'preprocessing', 'qda', 'svm', 'test', 'clone', 'pls']
  
  __version__ = '0.9-git'
  
subject: Fix spelling in dosctring.