title: GridSearchCV on LogisticRegression in scikit-learn
body: <p>I am trying to optimize a logistic regression function in scikit-learn by using a cross-validated grid parameter search, but I can't seem to implement it. </p>
  
  <p>It says that Logistic Regression does not implement a get_params() but on the documentation it says it does. How can I go about optimizing this function on my ground truth? </p>
  
  <pre><code>&gt;&gt;&gt; param_grid = {'C': [0.001, 0.01, 0.1, 1, 10, 100, 1000] }
  &gt;&gt;&gt; clf = GridSearchCV(LogisticRegression(penalty='l2'), param_grid)
  &gt;&gt;&gt; clf
  GridSearchCV(cv=None,
         estimator=LogisticRegression(C=1.0, intercept_scaling=1, dual=False, fit_intercept=True,
            penalty='l2', tol=0.0001),
         fit_params={}, iid=True, loss_func=None, n_jobs=1,
         param_grid={'C': [0.001, 0.01, 0.1, 1, 10, 100, 1000]},
         pre_dispatch='2*n_jobs', refit=True, score_func=None, verbose=0)
  &gt;&gt;&gt; clf = clf.fit(gt_features, labels)
  Traceback (most recent call last):
    File "&lt;stdin&gt;", line 1, in &lt;module&gt;
    File "/Library/Python/2.7/site-packages/scikit_learn-0.14_git-py2.7-macosx-10.8-x86_64.egg/sklearn/grid_search.py", line 351, in fit
      base_clf = clone(self.estimator)
    File "/Library/Python/2.7/site-packages/scikit_learn-0.14_git-py2.7-macosx-10.8-x86_64.egg/sklearn/base.py", line 42, in clone
      % (repr(estimator), type(estimator)))
  TypeError: Cannot clone object 'LogisticRegression(C=1.0, intercept_scaling=1, dual=False, fit_intercept=True,
            penalty='l2', tol=0.0001)' (type &lt;class 'scikits.learn.linear_model.logistic.LogisticRegression'&gt;): it does not seem to be a scikit-learn estimator a it does not implement a 'get_params' methods.
  &gt;&gt;&gt; 
  </code></pre>