title: Why is the logloss negative?
body: <p>I just applied the log loss in sklearn for logistic regression: <a href="http://scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html" rel="noreferrer">http://scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html</a></p>
  
  <p>My code looks something like this:</p>
  
  <pre><code>def perform_cv(clf, X, Y, scoring):
      kf = KFold(X.shape[0], n_folds=5, shuffle=True)
      kf_scores = []
      for train, _ in kf:
          X_sub = X[train,:]
          Y_sub = Y[train]
          #Apply 'log_loss' as a loss function
          scores = cross_validation.cross_val_score(clf, X_sub, Y_sub, cv=5, scoring='log_loss')
          kf_scores.append(scores.mean())
      return kf_scores
  </code></pre>
  
  <p>However, I'm wondering why the resulting logarithmic losses are negative. I'd expect them to be positive since in the documentation (see my link above) the log loss is multiplied by a -1 in order to turn it into a positive number.</p>
  
  <p>Am I doing something wrong here?</p>