title: scikit-learn: Is the cross validation score evaluating the log loss function?
body: <p>In python sklearn, I'm using stochastic gradient descent to perform multiclass classification, minimizing the log loss function.</p>
  
  <pre><code>clf = SGDClassifier(loss="log", penalty="l2")
  </code></pre>
  
  <p>When I perform cross validation over my test set, for each split of the data, I compute:</p>
  
  <pre><code>score = clf.fit(X_train, y_train).score(X_test, y_test)
  </code></pre>
  
  <p><strong>Is the score the evaluation of the loss function?</strong> </p>
  
  <p>For each cross validation split, my score is always 0.0. So does that mean my classifier correctly labeled my test data OR does it mean my accuracy is very low?</p>