old_contents: """
  Generalized linear models
  =========================
  
  scikits.learn.linear_model is a module to fit genelarized linear
  models.  It includes Ridge regression, Bayesian Regression, Lasso and
  Elastic Net estimators computed with Least Angle Regression and
  coordinate descent.
  
  It also implements Stochastic Gradient Descent related algorithms.
  
  See http://scikit-learn.sourceforge.net/modules/sgd.html and
  http://scikit-learn.sourceforge.net/modules/linear_model.html for
  complete documentation.
  """
  
  from .bayes import BayesianRidge, ARDRegression
  from .base import LinearRegression
  from .bayes import BayesianRidge, ARDRegression
  from .least_angle import LARS, LassoLARS, lars_path
  from .coordinate_descent import Lasso, ElasticNet, LassoCV, ElasticNetCV, \
                                  lasso_path, enet_path
  from .ridge import Ridge
  from .logistic import LogisticRegression
  
  from . import sparse
  from .stochastic_gradient import SGDClassifier, SGDRegressor
  from .base import Log, ModifiedHuber, Hinge, SquaredLoss, Huber
  
new_contents: """
  Generalized linear models
  =========================
  
  scikits.learn.linear_model is a module to fit genelarized linear
  models.  It includes Ridge regression, Bayesian Regression, Lasso and
  Elastic Net estimators computed with Least Angle Regression and
  coordinate descent.
  
  It also implements Stochastic Gradient Descent related algorithms.
  
  See http://scikit-learn.sourceforge.net/modules/sgd.html and
  http://scikit-learn.sourceforge.net/modules/linear_model.html for
  complete documentation.
  """
  
  from .base import LinearRegression, Log, ModifiedHuber, Hinge, \
       SquaredLoss, Huber
  
  from .bayes import BayesianRidge, ARDRegression
  from .least_angle import LARS, LassoLARS, lars_path
  from .coordinate_descent import Lasso, ElasticNet, LassoCV, ElasticNetCV, \
                                  lasso_path, enet_path
  from .stochastic_gradient import SGDClassifier, SGDRegressor
  from .ridge import Ridge
  from .logistic import LogisticRegression
  
  from . import sparse
  
  
subject: Remove duplicates in linear_model/__init__.py