title: Using sample_weight in GridSearchCV
body: <p>Is it possible to perform a <code>GridSearchCV</code> (to get the best SVM's C) and yet specify the <code>sample_weight</code> with scikit-learn?</p>
  <p>Here's my code and the error I'm confronted to:</p>
  <pre class="lang-py prettyprint-override"><code>gs = GridSearchCV(
      svm.SVC(C=1),
      [{
          'kernel': ['linear'],
          'C': [.1, 1, 10],
          'probability': [True],
          'sample_weight': sw_train,
      }]
  )
  
  gs.fit(Xtrain, ytrain)
  </code></pre>
  <blockquote>
  <p>&gt;&gt; ValueError: Invalid parameter sample_weight for estimator SVC</p>
  </blockquote>
  <hr>
  <p>Edit: I solved the issue by getting the latest scikit-learn version and using the following:</p>
  <pre><code>gs.fit(Xtrain, ytrain, fit_params={'sample_weight': sw_train})
  </code></pre>