title: Scikit learn-find best C & gamma by GridSearchCV () __I'm stuck
body: <p>I'm using GridSearchCV to get the best parameters (C &amp; gamma) for my SVR model and when I run it I get stuck for hours and no results, so what is wrong with this code?</p>
  
  <pre><code>from sklearn.model_selection import KFold
  C_range = np.logspace(-2, 10, 13)
  gamma_range = np.logspace(-9, 3, 13)
  param_grid = dict(gamma=gamma_range, C=C_range)
  cv = KFold(n_splits=5, shuffle=False, random_state=None)
  grid = GridSearchCV(SVR(kernel='rbf'), param_grid=param_grid, cv=cv)
  grid.fit(X, y)
  
  print("The best parameters are %s with a score of %0.2f"
    % (grid.best_params_, grid.best_score_))
  </code></pre>