Simplified prediction as suggested

Author: mvargas33

metric_learn/base_metric.py

@@ -602,9 +602,7 @@ def predict(self, triplets):
     prediction : `numpy.ndarray` of floats, shape=(n_constraints,)
       Predictions of the ordering of pairs, for each triplet.
     """
-    return np.array([-1 if (t <= 0) else 1 for t in
-                    self.decision_function(triplets)])
-    # return np.sign(self.decision_function(triplets))
+    return 2 * (self.decision_function(triplets) > 0) - 1
 
   def decision_function(self, triplets):
     """Predicts differences between sample distances in input triplets.